Your responsibilities will include providing technical leadership to guide strategic customers to successful implementations on big data projects, architecting production-level data pipelines, becoming a technical expert in an area such as data lake technology, big data streaming, or big data ingestion and workflows, assisting Solution Architects with more advanced aspects of the technical sale, and contributing to the Databricks Community.

To succeed in this role, you will need to have a strong background in software engineering and data engineering, with expertise in at least one of the following areas: software engineering/data engineering, data applications engineering, or deep specialty expertise in areas such as scaling big data workloads, migrating Hadoop workloads to the public cloud, or experience with large-scale data ingestion pipelines and data migrations.

You will also need to have a bachelor's degree in computer science, information systems, engineering, or equivalent experience through work experience, production programming experience in SQL and Python, Scala, or Java, and 2 years of professional experience with Big Data technologies and architectures.

XML job scraping automation by YubHub

In this role, you will lead product management for a core Lakeflow product area. You will own and drive all aspects of product management including vision, strategy, roadmap, execution, and go-to-marketing. In addition, you will partner closely with various Databricks product teams to enable Data Engineering for the overall Databrick product portfolio including data science, data warehousing, business intelligence, and machine learning products.

The impact you will have includes leading product management for one of the fastest growing products and businesses at Databricks, making company-wide impact by driving Data Engineering across the Databrick product portfolio, developing and deepening understanding of and expertise in Data Engineering, defining, shaping, and driving the future of data processing, data applications, and data pipelines, and owning the full life cycle of product development from ideation to requirements, development, pricing, launch, and go-to-market.

XML job scraping automation by YubHub

Anthropic's Accelerator Capacity Engineering (ACE) team manages one of the largest and fastest-growing accelerator fleets in the industry. As an engineer on ACE, you will build the production systems that power this work: data pipelines that ingest and normalize telemetry from heterogeneous cloud environments, observability tooling that gives the org real-time visibility into fleet health, and performance instrumentation that measures how efficiently every major workload uses the hardware it’s running on.

What This Team Owns

The team’s work spans three functional areas: data infrastructure, fleet observability, and compute efficiency. Depending on your background and interests, you’ll focus primarily in one, but the boundaries are fluid and the problems overlap:

Data Infrastructure

Collecting, normalizing, and serving the fleet-wide data that powers everything else. This means building pipelines that ingest occupancy and utilization telemetry from Kubernetes clusters, normalizing billing and usage data across cloud providers, and maintaining the BigQuery layer that the rest of the org queries against.

Fleet Observability

Making the state of the accelerator fleet legible and actionable in real time. This means building cluster health tooling, capacity planning platforms, alerting on occupancy drops and allocation problems, and driving systemic improvements to scheduling and fragmentation.

Compute Efficiency

Measuring and improving how effectively every major workload uses the hardware it’s running on. This means instrumenting utilization metrics across training, inference, and eval systems, building benchmarking infrastructure, establishing per-config baselines, and collaborating directly with system-owning teams to close efficiency gaps.

What You’ll Do

• Build and operate data pipelines that ingest accelerator occupancy, utilization, and cost data from multiple cloud providers into BigQuery.
• Develop and maintain observability infrastructure , Prometheus recording rules, Grafana dashboards, and alerting systems , that surface actionable signals about fleet health, occupancy, and efficiency.
• Instrument and analyze compute efficiency metrics across training, inference, and eval workloads.
• Build internal tooling and platforms that enable capacity planning, workload attribution, and cluster debugging.
• Operate Kubernetes-native systems at scale , deploying data collection agents, managing workload labeling infrastructure, and understanding how taints, reservations, and scheduling affect capacity.
• Normalize and reconcile data across heterogeneous sources , including AWS, GCP, and Azure billing exports, vendor-specific telemetry formats, and internal systems with different schemas and billing arrangements.

You May Be a Good Fit If You Have

• 5+ years of software engineering experience with a strong track record building and operating production systems.
• Kubernetes fluency at operational depth , you’ve operated production K8s at meaningful scale, not just written manifests.
• Data pipeline engineering experience , designing, building, and owning the full lifecycle of production data pipelines.
• Observability tooling experience , Prometheus, PromQL, and Grafana are in the critical path for this team.
• Python and SQL at production quality.
• Familiarity with at least one major cloud provider (AWS, GCP, or Azure) at the infrastructure level , compute, billing, usage APIs, cost management tooling.

Strong Candidates May Also Have

• Multi-cloud data ingestion experience , especially working with AWS and GCP APIs, billing exports, or vendor-specific telemetry formats.
• Accelerator infrastructure familiarity , GPU metrics (DCGM), TPU utilization, Trainium power and utilization metrics, or experience working with ML training/inference systems at the hardware level.
• Performance engineering and benchmarking experience , building benchmark harnesses, establishing baselines, reasoning about compute efficiency (FLOPs utilization, memory bandwidth, interconnect throughput), and working with system teams to diagnose and improve performance.
• Data-as-product thinking , experience building internal data products with self-service access, schema contracts, API serving, documentation,

XML job scraping automation by YubHub

Brex is a finance platform that enables companies to spend smarter and move faster in over 200 markets. It combines global corporate cards and banking with intuitive spend management, bill pay, and travel software.

Tens of thousands of the world's best companies run on Brex, including DoorDash, Coinbase, Robinhood, Zoom, Plaid, Reddit, and SeatGeek.

Working at Brex allows you to push your limits, challenge the status quo, and collaborate with some of the brightest minds in the industry.

We're committed to building a diverse team and inclusive culture and believe your potential should only be limited by how big you can dream.

We make this a reality by empowering you with the tools, resources, and support you need to grow your career.

Data at Brex

The Data organization develops insights, models, and data infrastructure for teams across Brex, including Sales, Marketing, Product, Engineering, and Operations.

Our Data Scientists, Analysts, and Engineers work together to make data,and insights derived from data,a core asset across the company.

What you'll do

As a senior Data Analyst (DA III), you will own the end-to-end analytics lifecycle for one or more business areas at Brex.

You'll go beyond building dashboards,you'll frame the right questions, design rigorous analyses, apply statistical methods, and translate your findings into clear recommendations for leadership.

You will also serve as a technical leader on the Data Analytics team, mentoring more junior analysts and helping define the standards and best practices that elevate the team's work.

This role sits at the intersection of analytics, analytics engineering, and business strategy.

You'll work in a modern data stack environment and partner closely with Data Scientists, Data Engineers, and senior leaders across the organization.

Where you'll work

This role will be based in our San Francisco office.

We are a hybrid environment that combines the energy and connections of being in the office with the benefits and flexibility of working from home.

We currently require a minimum of three coordinated days in the office per week, Monday, Wednesday and Thursday.

As a perk, we also have up to four weeks per year of fully remote work!

Responsibilities

• Own the analytics lifecycle for assigned business areas: from problem framing and data sourcing through analysis, insight generation, and stakeholder presentation.

• Build and maintain dashboards and self-service reporting tools that enable business teams to independently track performance, identify risks, and make data-driven decisions.

• Write production-quality SQL and Python code to extract, transform, and analyze data at scale.

• Collaborate with Data Engineers and Data Scientists to develop and maintain analytical data models, improve data pipelines, and ensure data quality across the organization.

• Partner with leadership across Sales, Operations, Product, Finance, and other departments to identify high-impact analytical opportunities and deliver actionable recommendations.

• Mentor other data analysts and contribute to the development of team standards, documentation, code review practices, and analytical frameworks.

• Proactively identify gaps in data infrastructure, propose improvements, and contribute to the evolution of the team’s tooling and processes.

Requirements

• 5+ years of experience in data analytics, business intelligence, or a related quantitative role.

• 3+ years of experience partnering directly with Sales, Operations, Product, or equivalent business teams as an embedded analytics partner.

• Advanced SQL proficiency, including CTEs, window functions, performance optimization, and working across complex data models.

• Proficiency in Python for data analysis, automation, and modeling (Pandas, NumPy, scikit-learn, or similar).

• Experience with cloud data warehouses, particularly Snowflake (BigQuery and Databricks also valued).

• Hands-on experience with BI and data visualization tools (Looker, Tableau, Hex, or similar).

• Strong stakeholder management skills,proven ability to present complex technical findings to non-technical audiences.

• Experience with generative AI and LLM-based tools (Claude Code, Cursor, GitHub Copilot) to perform and accelerate analyses, automated reporting, and build self-service data tools.

Bonus points

• Demonstrated experience applying statistical methods to business problems (e.g., regression, classification, A/B testing).

• Experience with dbt for data modeling and transformation.

• Experience building and maintaining data pipelines using orchestration tools such as Airflow.

• Experience working with APIs for data ingestion and integration.

• Familiarity with version control systems (Git).

• Experience in fintech, financial services, or payments.

• Track record of leading cross-functional analytics projects from scoping through delivery.

Compensation

The expected salary range for this role is $114,192 - $142,740.

However, the starting base pay will depend on a number of factors including the candidate’s location, skills, experience, market demands, and internal pay parity.

Depending on the position offered, equity and other forms of compensation may be provided as part of a total compensation package.

XML job scraping automation by YubHub

We are seeking senior software engineers with specialization in database and stream processing who can help us fulfill the goal of our global datastore strategy and establish communication models for our data flow. This individual will work with a team of mixed skilled engineers and have the opportunity to work on the full range of rewarding challenges that come with the business of building a cloud in a communicative, supportive, and high-performing environment.

As a member of the Data Platform Team you will have the opportunity to:

• Design and implement the platform to deliver data to teams with a focus on providing managed solutions through APIs
• Participate in operations and scaling of relational data platforms
• Develop a stream processing architecture and solve for scalability and reliability
• Improve the performance, security, reliability, and scalability of our data platforms and related services, and participate in the team’s on-call rotation
• Establish guidelines and guard rails for data access and storage for stakeholder teams
• Ensure compliance with standards for data protection regulation
• Grow, change, invest in your teammates, be invested-in, share your ideas, listen to others, be curious, have fun, and, above all, be yourself

The ideal candidate will have 5+ years of experience in a software or infrastructure engineering industry, with experience operating services in production and at scale and familiarity with reliability engineering concepts such as different types of testing, progressive deployments, error budgets, observability, and fault-tolerant design.

The base salary range for this role is $175,000 to $210,000. The starting salary will be determined based on job-related knowledge, skills, experience, and market location.

XML job scraping automation by YubHub

Brex is the intelligent finance platform that enables companies to spend smarter and move faster in more than 200 markets. By combining global corporate cards and banking with intuitive spend management, bill pay, and travel software, Brex enables founders and finance teams to accelerate operations, gain real-time visibility, and control spend effortlessly.

Tens of thousands of the world's best companies run on Brex, including DoorDash, Coinbase, Robinhood, Zoom, Plaid, Reddit, and SeatGeek.

Working at Brex allows you to push your limits, challenge the status quo, and collaborate with some of the brightest minds in the industry. We’re committed to building a diverse team and inclusive culture and believe your potential should only be limited by how big you can dream. We make this a reality by empowering you with the tools, resources, and support you need to grow your career.

Data at Brex

The Data organization develops insights, models, and data infrastructure for teams across Brex, including Sales, Marketing, Product, Engineering, and Operations. Our Data Scientists, Analysts, and Engineers work together to make data,and insights derived from data,a core asset across the company.

What you’ll do

As a senior Data Analyst (DA III), you will own the end-to-end analytics lifecycle for one or more business areas at Brex. You’ll go beyond building dashboards,you’ll frame the right questions, design rigorous analyses, apply statistical methods, and translate your findings into clear recommendations for leadership. You will also serve as a technical leader on the Data Analytics team, mentoring more junior analysts and helping define the standards and best practices that elevate the team’s work.

This role sits at the intersection of analytics, analytics engineering, and business strategy. You’ll work in a modern data stack environment and partner closely with Data Scientists, Data Engineers, and senior leaders across the organization.

Where you’ll work

This role will be based in our New York office. We are a hybrid environment that combines the energy and connections of being in the office with the benefits and flexibility of working from home. We currently require a minimum of three coordinated days in the office per week, Monday, Wednesday and Thursday. As a perk, we also have up to four weeks per year of fully remote work!

Responsibilities

• Own the analytics lifecycle for assigned business areas: from problem framing and data sourcing through analysis, insight generation, and stakeholder presentation.

• Build and maintain dashboards and self-service reporting tools that enable business teams to independently track performance, identify risks, and make data-driven decisions.

• Write production-quality SQL and Python code to extract, transform, and analyze data at scale.

• Collaborate with Data Engineers and Data Scientists to develop and maintain analytical data models, improve data pipelines, and ensure data quality across the organization.

• Partner with leadership across Sales, Operations, Product, Finance, and other departments to identify high-impact analytical opportunities and deliver actionable recommendations.

• Mentor other data analysts and contribute to the development of team standards, documentation, code review practices, and analytical frameworks.

• Proactively identify gaps in data infrastructure, propose improvements, and contribute to the evolution of the team’s tooling and processes.

Requirements

• 5+ years of experience in data analytics, business intelligence, or a related quantitative role.

• 3+ years of experience partnering directly with Sales, Operations, Product, or equivalent business teams as an embedded analytics partner.

• Advanced SQL proficiency, including CTEs, window functions, performance optimization, and working across complex data models.

• Proficiency in Python for data analysis, automation, and modeling (Pandas, NumPy, scikit-learn, or similar).

• Experience with cloud data warehouses, particularly Snowflake (BigQuery and Databricks also valued).

• Hands-on experience with BI and data visualization tools (Looker, Tableau, Hex, or similar).

• Strong stakeholder management skills,proven ability to present complex technical findings to non-technical audiences.

• Experience with generative AI and LLM-based tools (Claude Code, Cursor, GitHub Copilot) to perform and accelerate analyses, automated reporting, and build self-service data tools.

Bonus points

• Demonstrated experience applying statistical methods to business problems (e.g., regression, classification, A/B testing).

• Experience with dbt for data modeling and transformation.

• Experience building and maintaining data pipelines using orchestration tools such as Airflow.

• Experience working with APIs for data ingestion and integration.

• Familiarity with version control systems (Git).

• Experience in fintech, financial services, or payments.

• Track record of leading cross-functional analytics projects from scoping through delivery.

Compensation

The expected salary range for this role is $114,192 - $142,740. However, the starting base pay will depend on a number of factors including the candidate’s location, skills, experience, market demands, and internal pay parity. Depending on the position offered, equity and other forms of compensation may be provided as part of a total compensation package.

XML job scraping automation by YubHub

At Cloudflare, we are on a mission to help build a better Internet. Today the company runs one of the world's largest networks that powers millions of websites and other Internet properties for customers ranging from individual bloggers to SMBs to Fortune 500 companies.

We protect and accelerate any Internet application online without adding hardware, installing software, or changing a line of code. Internet properties powered by Cloudflare all have web traffic routed through its intelligent global network, which gets smarter with every request. As a result, they see significant improvement in performance and a decrease in spam and other attacks.

Responsibilities

As a Software Engineer: Distributed Systems, you will be part of a Resiliency Organization responsible for the core services that power Cloudflare's global operations. We are looking for engineers to join the Infrastructure Intelligence team and shape the transition toward model-driven network orchestration.

The team is building a cutting-edge 'Maintenance Coordination System', powered by an infrastructure dependency graph of one of the world's largest physical networks. This is a foundational step towards designing intelligent, autonomous systems that will transform the orchestration of Cloudflare's network.

It forms the basis of many future projects to build the core data structures and services required to ensure our network optimization, network forecasting, and capacity planning are the state of the art. By creating the robust primitives for global coordination today, you will be enabling the next generation of data-driven infrastructure at Cloudflare.

This is a unique opportunity to work on complex, globally distributed systems which underpin all Cloudflare products.

Technologies we use:

• Cloudflare Workers, Workers KV, R2, and Durable Objects

• Kubernetes

• Go, Typescript, Python

• For service monitoring we use Prometheus, Grafana and Sentry

Requirements

• A degree in Computer Science, Engineering, Mathematics, Statistics or related field; OR have relevant background/experience to the field.

• Programming experience in Go, or similar languages

• Experience in designing and implementing secure and highly-available distributed systems

• Experience (and love) for debugging to ensure the system works in all cases

• Experience with a continuous integration workflow and using source control (we use git)

• Experience with continuous delivery and deployment of a k8s hosted application

• Understanding of security issues and responsibilities

• Experience with monitoring, alerting and debugging high volume production systems

• Fluent in analyses of data sets such as logs

• Strong English language oral and written communications skills

• Designing and building APIs

• Experience with the Cloudflare development stack is a plus

Examples of desirable skills, knowledge and experience

• At least 4 years of hands-on software development experience on meaningfully complex systems.

• Experience with graph theory and building services for graph generation, storage and retrieval.

• An understanding of the systems architecture required to scale machine learning model-driven decision engines in a production environment

• Experience building both backend systems and frontend widgets.

• Ability to contribute to planning, development, and execution to meet commitments and deliver with predictability.

• Experience implementing tools, processes, internal instrumentation, and methodologies.

• Comfortable working on projects with tight deadlines and short release cycles.

• Strong verbal and written English language skills.

• Experience with DCIM, CMDB, IPAM, and other Data Center and Asset Lifecycle Management tools is a plus.

• Experience with data ingestion and analysis - pulling metrics from hundreds of edge data centers.

Compensation

For Washington D.C. based hires: Estimated annual salary of $140,000 - 172,000.

Equity

This role is eligible to participate in Cloudflare's equity plan.

Benefits

Cloudflare offers a complete package of benefits and programs to support you and your family. Our benefits programs can help you pay health care expenses, support caregiving, build capital for the future and make life a little easier and fun!

The below is a description of our benefits for employees in the United States, and benefits may vary for employees based outside the U.S.

Health & Welfare Benefits

• Medical/Rx Insurance

• Dental Insurance

• Vision Insurance

• Flexible Spending Accounts

• Commuter Spending Accounts

• Fertility & Family Forming Benefits

• On-demand mental health support and Employee Assistance Program

• Global Travel Medical Insurance

Financial Benefits

• Short and Long Term Disability Insurance

• Life & Accident Insurance

• 401(k) Retirement Savings Plan

• Employee Stock Participation Plan

Time Off

• Flexible paid time off covering vacation and sick leave

• Leave programs, including parental, pregnancy health, medical, and bereavement leave

What Makes Cloudflare Special?

We're not just a highly ambitious, large-scale technology company. We're a highly ambitious, large-scale technology company with a soul. Fundamental to our mission to help build a better Internet is protecting the free and open Internet.

Project Galileo: Since 2014, we've equipped more than 2,400 journalism and civil society organizations in 111 countries with powerful tools to defend themselves against attacks that would otherwise censor their work, technology already used by Cloudflare's enterprise customers--at no cost.

Athenian Project: In 2017, we created the Athenian Project to ensure that state and local governments have the highest level of protection and reliability for free, so that their constituents have access to election information and voter registration. Since the project, we've provided services to more than 425 local government election websites in 33 states.

1.1.1.1: We released 1.1.1.1 to help fix the foundation of the Internet by building a faster, more secure and privacy-centric public DNS resolver. This is available publicly for everyone to use - it is the first consumer-focused service Cloudflare has ever built.

XML job scraping automation by YubHub

As a Staff Engineer, AI Security on the AppSec team, you'll lead autonomous defense for the AI lifecycle. Build multi-agent frameworks and secure gateways while integrating real-time security gates and identity standards. By mentoring Security and R&D to define the MLSecOps roadmap, you'll ensure a 'secure-by-default' future for agentic workflows and resilient AI innovation.

Responsibilities:

Serve as the primary subject matter expert for all AI and machine learning security initiatives across security and R&D.

Design and manage AI gateways to provide a centralized control plane for authentication and authorization and rate limiting across all model and tool interactions.

Build and maintain an autonomous security agentic framework that utilizes multi agent orchestration for end to end investigation and alert triage and remediation.

Develop agentic identity models using OAuth 2.1 to propagate identity across trust boundaries and prevent the confused deputy problem.

Help govern the AI augmented software development lifecycle by integrating real time security gates into the developer environment and CI/CD pipeline.

Manage Agentic Security Solutions that secure AI lifecycle and manage AI workloads at runtime.

Author company wide AI security standards and implement these security checks across Twilio's stack.

Implement human in the loop checkpoints and transactional safety protocols for high impact or destructive agentic actions.

Partner with engineering leadership to set the long term roadmap for identity centric security and automated posture management.

Act as a knowledge multiplier by mentoring security engineers and developing secure by default paved road templates for R&D teams

Qualifications:

8+ years of experience in security engineering with at least 3 years focused on AI or machine learning security operations (MLSecOps).

Expertise in orchestrating multi-agent systems with AWS Strands, LangGraph, and CrewAI, specializing in runtime isolation, PII redaction, and defending against indirect prompt injection in agentic environments.

Hands-on experience with AI-specific frameworks (e.g., MITRE ATLAS, MAESTRO, OWASP Top 10 for LLMs/Agents/MCP) to threat model and defend against a wide spectrum of risks, including direct/indirect prompt injection, training data poisoning, tool poisoning, and data exfiltration within agentic workflows.

Proficiency in securing end-to-end AI pipelines, from data ingestion and training to model deployment and monitoring.

Strong communication skills to translate complex AI risks into actionable business logic for stakeholders.

Desired:

Hands-on experience in modern application security tooling including SAST and SCA and DAST with experience adapting these tools to catch AI specific vulnerabilities like indirect prompt injection.

Expertise in identity standards including OAuth 2.1 and PKCE.

Experience with AI Red Teaming and conducting adversarial simulations against Large Language Models (LLMs) and agentic systems.

Proficiency in at least one general programming language (Python, Go, etc) with experience in container security and workload isolation.

Proven ability to operate with autonomy and drive high impact outcomes in ambiguous environments by identifying and executing on critical projects without predefined roadmaps or direct supervision.

XML job scraping automation by YubHub

You will translate business and technical requirements into scalable, outcome-driven solutions built on the Elastic Stack. You will lead end-to-end delivery of customer engagements , from discovery and design through implementation, enablement, and optimisation. You will partner with customers to architect, deploy, and operationalise Elastic solutions that drive measurable value and adoption.

You will provide technical oversight, guidance, and enablement to customers and teammates throughout project lifecycles. You will collaborate cross-functionally with Sales, Product, Engineering, and Support to ensure successful outcomes and continuous improvement. You will capture and share best practices, lessons learned, and solution patterns across the Elastic Services community.

You will guide customers in using Elastic Agents, Beats, Logstash time-series data ingestion, stream processing, and normalisation, and related technologies. You will design and implement custom dashboards, visualisations, and alerting for critical observability use cases in Kibana. You will optimise ingestion pipelines for performance, scalability, and resiliency at enterprise scale.

You will have 5+ years as a consultant, architect, or engineer with expertise in observability, monitoring, or related domains. You will have strong experience with time-series data ingestion and processing, including pipelines with Elastic Agents, Beats, and Logstash. You will have knowledge of messaging queues (Kafka, Redis) and ingestion optimisation strategies.

You will have understanding of observability concepts like distributed tracing, metrics pipelines, log aggregation, anomaly detection, SLOs/SLIs. You will have experience with one or more: Kubernetes, cloud platforms (AWS, Azure, GCP), or infrastructure as code. You will have familiarity with Elastic Common Schema (ECS), data parsing, and normalisation.

You will have proven experience deploying Elastic Observability (APM, UEM, logs, metrics, infra, network monitoring) or similar solutions at enterprise scale. You will have hands-on expertise in distributed systems and large-scale infrastructure. You will have ability to design and build dashboards, visualisations, and alerting thresholds that drive actionable insights.

You will have experience with Kubernetes, Linux, Java, databases, Docker, AWS/Azure/GCP, VMs, Lucene. You will have strong communication and presentation skills, with experience engaging directly with customers. You will have a Bachelor’s, Master’s, or PhD in Computer Science, Engineering, or related field, or equivalent experience.

You will be comfortable working in highly distributed teams, both remote and on-site when needed. You may require significant travel to customer sites to support engagements and solution implementations; candidates should be comfortable with varying levels of travel based on business needs.

XML job scraping automation by YubHub

You'll collaborate with Elastic’s Professional Services, Engineering, Product, and Sales teams to accelerate adoption of the Elastic Observability platform, ensuring customers maximise the value of their data while achieving business outcomes. This is a highly impactful role, with opportunities to guide strategy, lead complex implementations, and mentor both customers and teammates.

Key responsibilities include:

• Translating business and technical requirements into scalable, outcome-driven solutions built on the Elastic Stack.
• Leading end-to-end delivery of customer engagements , from discovery and design through implementation, enablement, and optimisation.
• Partnering with customers to architect, deploy, and operationalise Elastic solutions that drive measurable value and adoption.
• Providing technical oversight, guidance, and enablement to customers and teammates throughout project lifecycles.
• Collaborating cross-functionally with Sales, Product, Engineering, and Support to ensure successful outcomes and continuous improvement.
• Capturing and sharing best practices, lessons learned, and solution patterns across the Elastic Services community.
• Contributing to internal enablement, mentoring, and a culture of continuous learning and collaboration

Required skills include:

• 5+ years as a consultant, architect, or engineer with expertise in observability, monitoring, or related domains.
• Expertise in the Telecommunications domain, especially with Mobile networks and devices.
• Strong experience with time-series data ingestion and processing, including pipelines with Elastic Agents, Beats, and Logstash.
• Knowledge of messaging queues (Kafka, Redis) and ingestion optimisation strategies.
• Understanding of observability concepts like distributed tracing, metrics pipelines, log aggregation, anomaly detection, SLOs/SLIs.
• Experience with one or more: Kubernetes, cloud platforms (AWS, Azure, GCP), or infrastructure as code.
• Familiarity with Elastic Common Schema (ECS), data parsing, and normalisation.
• Proven experience deploying Elastic Observability (APM, UEM, logs, metrics, infra, network monitoring) or similar solutions at enterprise scale.
• Hands-on expertise in distributed systems and large-scale infrastructure.
• Ability to design and build dashboards, visualisations, and alerting thresholds that drive actionable insights.
• Experience with Kubernetes, Linux, Java, databases, Docker, AWS/Azure/GCP, VMs, Lucene.
• Strong communication and presentation skills, with experience engaging directly with customers.
• Bachelor’s, Master’s, or PhD in Computer Science, Engineering, or related field, or equivalent experience.
• Comfortable working in highly distributed teams, both remote and on-site when needed.
• May require significant travel to customer sites to support engagements and solution implementations; candidates should be comfortable with varying levels of travel based on business needs.

XML job scraping automation by YubHub

XML job scraping automation by YubHub

Reporting to the Head of Customer Success & Delivery, this role will own how customers integrate with the Zus platform. They’ll be responsible for ensuring healthcare organisations and digital health builders can reliably ingest data, connect EHR systems, and deploy applications powered by Zus APIs.

This leader will oversee teams responsible for forward deployment engineering, and technical enablement, working closely with customer engineering teams to integrate Zus into production environments and connect to data networks.

You will guide customers through the complexity of healthcare interoperability, helping them translate real-world workflows into scalable integrations built on Zus.

This is a hands-on player-coach role. You will lead the team while also personally engaging in complex implementations, architecture discussions, and customer deployments.

You will champion the use of AI tools, automation frameworks, and reusable integration patterns to dramatically improve how quickly and reliably customers connect to the Zus platform.

The ideal candidate combines deep experience in healthcare interoperability, enterprise software implementations, API platforms, and AI-enabled engineering workflows with the leadership skills required to scale a delivery organisation.

Key responsibilities:

• Lead implementation and technical delivery - Own the technical delivery lifecycle following contract signature through production deployment and early adoption
• Lead and grow a team of Solutions Engineers and Forward Deployed Engineers - Develop career paths, performance expectations, and development plans for the team to ensure excellent execution of goals
• Ensure consistent, high-quality execution across multiple concurrent enterprise implementations
• Establish best practices for onboarding, implementation, integration, and go-live readiness
• Set customers up for success across multiple different high priority use cases
• Ensure customers achieve rapid time-to-value from the Zus platform

Act as player-coach for complex implementations - Personally engage on strategic or technically complex customer deployments

Guide integrations involving FHIR, HL7, CCD, APIs, SFTP pipelines, and EHR platforms

Troubleshoot complex interoperability and data pipeline issues

Work directly with engineering teams to deploy and operationalize Zus products

Serve as a trusted technical advisor to customer technical and operational stakeholders

Drive forward deployed engineering - Support customers in building production-grade applications and workflows on top of Zus APIs

Help customers operationalize clinical and operational data across care delivery workflows

Lead the development of reference architectures and deployment patterns

Identify integration opportunities that accelerate product adoption and expansion

Delivery training and technical enablement - Oversee technical onboarding and training programs for new customers

Enable customer engineering and product teams to effectively build on the Zus platform

Develop documentation, workshops, and enablement resources for technical users

Drive AI-enabled implementation and automation - Lead the adoption of AI tools and automation frameworks across the delivery organisation

Identify opportunities to automate manual implementation work using LLMs, scripting, and developer tooling

Develop reusable automation patterns for all parts of the Zus ecosystem

Help customers leverage Zus data to power AI-enabled workflows and analytics applications

Partner with Product and Engineering - Translate customer implementation patterns into platform improvement

Participate in technical discussions to find reusable integration patterns that can be embedded directly into the Zus platform

Communicate customer needs to the Product & Engineering teams

You're a good fit because you have:

• 10+ years of experience in technical implementation, solutions engineering, systems integration, or professional services leadership, preferably in healthtech, SaaS, or enterprise software
• Proven experience leading customer-facing teams and scaling implementation or professional services functions
• Deep expertise in healthcare data interoperability, including FHIR, HL7, CCD, and EHR integrations
• Strong understanding of APIs, data ingestion pipelines (ETL, JSON, CSV), and modern data platforms (e.g., Snowflake)
• Experience designing scalable implementation frameworks and reusable integration patterns
• Familiarity with secure environments and compliance frameworks (HIPAA, SOC 2)
• Executive presence and the ability to build trust with both technical and non-technical stakeholders
• Strong strategic thinking paired with a willingness to dive into complex technical or delivery challenges when needed
• A self-starter mindset and comfort operating in a fast-paced, evolving startup environment
• Passion for improving healthcare through better access to and use of data
• Willingness to travel up to ~25% for customer engagements, industry events, and company meetings
• Bachelor’s degree in Business, Engineering, or a related field (advanced degree a plus)

Additional Information:

We will offer you...

• Competitive compensation that reflects the value you bring to the team a combination of cash and equity
• Robust benefits that include health insurance, wellness benefits, 401k with a match, unlimited PTO
• Opportunity to work alongside a passionate team that is determined to help change the world (and have fun doing it)

XML job scraping automation by YubHub

Responsibilities

• Scale and optimise our trading systems across multiple energy markets
• Build and maintain integrations with exchanges and data providers
• Develop new and improve existing proprietary trading technology for risk management, P&L tracking, and weather forecasting
• Ensure seamless integration between trading operations and retail customer platforms (usage data, billing, tariff management)
• Work closely with quants and traders, putting trading strategies into production and building new tools
• Mentor and grow a high-performing team of engineers

Requirements

• Proven track record as a senior software engineer, tech lead, or engineering manager within trading
• 5+ years of experience as a software engineer, including 2+ years in a technical leadership role
• Hands-on experience with cloud infrastructure and event-driven architectures
• Strong understanding of trading system architecture, including market data ingestion, execution engines, pricing, and risk systems
• Track record of setting technical vision and aligning engineering initiatives with broader business goals

Benefits

• Competitive salary and an equity sign-on bonus
• Biannual bonus scheme
• Fully expensed tech to match your needs
• Paid annual leave
• Breakfast and dinner allowance for office based employees

XML job scraping automation by YubHub

Responsibilities

• Scale and optimize our trading systems across multiple energy markets
• Build and maintain integrations with exchanges and data providers
• Develop new and improve existing proprietary trading technology for risk management, P&L tracking, and weather forecasting
• Ensure seamless integration between trading operations and retail customer platforms (usage data, billing, tariff management)
• Work closely with quants and traders, putting trading strategies into production and building new tools
• Mentor and grow a high-performing team of engineers

Requirements

• Proven track record as a senior software engineer, tech lead, or engineering manager within trading
• 5+ years of experience as a software engineer, including 2+ years in a technical leadership role
• Hands-on experience with cloud infrastructure and event-driven architectures
• Strong understanding of trading system architecture, including market data ingestion, execution engines, pricing, and risk systems
• Track record of setting technical vision and aligning engineering initiatives with broader business goals

Benefits

• Competitive salary and an equity sign-on bonus
• Biannual bonus scheme
• Fully expensed tech to match your needs
• Paid annual leave
• Breakfast and dinner allowance for office-based employees

XML job scraping automation by YubHub

Product Manager – Private Markets Secondaries Data & Analytics

This role sits within Preqin, a part of BlackRock. Preqin plays a key role in how we are revolutionizing private markets data and technology for clients globally, complementing our existing Aladdin technology platform to deliver investment solutions for the whole portfolio.

About the team

Preqin’s Limited Partners Product Group is a cross-functional team within Aladdin Product, responsible for creating innovative data, analytics and workflow products for our clients investing in Private Markets. We are seeking a Product Manager to join the team and work directly with a multi-disciplinary team using the latest technologies to build out secondaries data and analytics products geared towards helping our clients make better investment decisions.

Job overview

Secondaries is a rapidly growing part of private markets, but still very opaque and ripe for innovation. This role will focus on building new data, analytics and workflow products for the secondaries ecosystem, and helping our clients better understand market activity, benchmark transactions, and identify and value the assets being traded.

Responsibilities

• Define the product vision and strategy for your area, working closely with senior stakeholders and your cross-functional team to identify how to deliver on our strategic goals.

• Lead continuous discovery with secondaries advisors, investors, and internal teams—understanding workflows upstream and downstream of private markets data usage.

• Translate complex, ambiguous problems into clear product requirements (PRDs, epics, user stories), prioritised roadmaps, and measurable outcomes.

• Build data-first product capabilities across analytics, benchmarking, and automated workflows.

• Identify and track the right metrics for your area and your customers and use those metrics to make our products better.

• Work closely and collaboratively with engineers and designers – you’ll get everyone aligned around a problem, work together on how to solve it, and then execute effectively.

• Build iteratively and share feedback with customers continuously as you build and evolve the product.

• Develop yourself and the people around you – share what you’ve learned, and work with colleagues to find ways to do things better.

You are a good fit if:

• You care about customers deeply – you’re obsessed with finding out what their problems are, and how we are going to solve them.

• You’re a strong executor, with a track record of getting product to customers quickly and iteratively.

• You’re evidence-based, using data, customer feedback and market insight to build industry-leading products.

• You’re comfortable in ambiguity and enjoy zero-to-one work—turning unclear inputs into crisp plans and shipped outcomes.

• You can partner effectively across engineering, design, data, commercial and senior stakeholders to drive alignment and delivery.

• You take ownership and responsibility for problems, and if you see something wrong, you make it better.

Nice to have:

• Familiarity with private markets (PE/VC/Real Assets) and/or secondaries.

• Experience with data partnerships, data ingestion, entity resolution/identifiers, or analytics/benchmarking products.

• Comfort working with data directly (e.g. Excel, SQL) and using analysis to guide prioritisation.

Our benefits

To help you stay energized, engaged and inspired, we offer a wide range of employee benefits including: retirement investment and tools designed to help you in building a sound financial future; access to education reimbursement; comprehensive resources to support your physical health and emotional well-being; family support programs; and Flexible Time Off (FTO) so you can relax, recharge and be there for the people you care about.

Our hybrid work model

BlackRock’s hybrid work model is designed to enable a culture of collaboration and apprenticeship that enriches the experience of our employees, while supporting flexibility for all. Employees are currently required to work at least 4 days in the office per week, with the flexibility to work from home 1 day a week. Some business groups may require more time in the office due to their roles and responsibilities. We remain focused on increasing the impactful moments that arise when we work together in person – aligned with our commitment to performance and innovation. As a new joiner, you can count on this hybrid model to accelerate your learning and onboarding experience here at BlackRock.

About BlackRock

At BlackRock, we are all connected by one mission: to help more and more people experience financial well-being. Our clients, and the people they serve, are saving for retirement, paying for their children’s educations, buying homes and starting businesses. Their investments also help to strengthen the global economy: support businesses small and large; finance infrastructure projects that connect and power cities; and facilitate innovations that drive progress.

This mission would not be possible without our smartest investment – the one we make in our employees. It’s why we’re dedicated to creating an environment where our colleagues feel welcomed, valued and supported with networks, benefits and development opportunities to help them thrive.

XML job scraping automation by YubHub

We are looking for an innovative hands-on technologist to run Data Operations for one of the largest global FinTech's. This is a new role that will transform how we manage and process high quality data at scale and reflects our commitment to invest in an Enterprise Data Platform to unlock our data strategy for BlackRock and our Aladdin Client Community.

Key responsibilities

The ideal candidate will be a high-energy, technology and data driven individual who has a track record of leading and doing the day to day operations.

• Ensure on time high quality data delivery with a single pane of glass for data pipeline observability and support
• Live and breathe best practices of data ops such as culture, processes and technology
• Partner cross-functionally to enhance existing data sets, eliminating manual inputs and ensuring high quality, and onboarding new data sets
• Lead change while ensuring daily operational excellence, quality, and control
• Build and maintain deep alignment with key internal partners on ops tooling and engineering
• Foster an agile collaborative culture which is creative open, supportive, and dynamic

Knowledge and Experience

• 8+ years’ experience in hands-on data operations including data pipeline monitoring and engineering
• Technical expert including experience with data processing, orchestration (Airflow) data ingestion, cloud-based databases/warehousing (Snowflake) and business intelligence tools
• Champion the adoption of AI-enabled capabilities across Data Operations, including anomaly detection, predictive issue management, and automated operational insights to improve resilience, scale, and client experience.
• The ability to operate and monitor large data sets through the data lifecycle, including the tooling and observability required to ensure data quality and control at scale
• Experience implementing, monitoring, and operating data pipelines that are fast, scalable, reliable, and accurate
• Understanding of modern-day data highways, the associated challenges, and effective controls
• Passionate about data platforms, data quality and everything data
• Practical and detailed oriented operations leader
• Inquisitive leader who will bring new ideas that challenge the status quo
• Ability to navigate a large, highly matrixed organization
• Strong presence with clients

Our benefits

To help you stay energized, engaged and inspired, we offer a wide range of employee benefits including: retirement investment and tools designed to help you in building a sound financial future; access to education reimbursement; comprehensive resources to support your physical health and emotional well-being; family support programs; and Flexible Time Off (FTO) so you can relax, recharge and be there for the people you care about.

Our hybrid work model

BlackRock’s hybrid work model is designed to enable a culture of collaboration and apprenticeship that enriches the experience of our employees, while supporting flexibility for all. Employees are currently required to work at least 4 days in the office per week, with the flexibility to work from home 1 day a week. Some business groups may require more time in the office due to their roles and responsibilities. We remain focused on increasing the impactful moments that arise when we work together in person – aligned with our commitment to performance and innovation. As a new joiner, you can count on this hybrid model to accelerate your learning and onboarding experience here at BlackRock.

XML job scraping automation by YubHub

This role sits within Aladdin Platform Engineering and focuses on the infrastructure and platform services required to support machine learning models, large language models (LLMs), and emerging AI capabilities in production. The successful candidate will work closely with AI Engineers, Data Scientists, Platform Engineers, Security, and Product partners to deliver resilient, cloud native AI platforms in a highly regulated environment.

Key Responsibilities

• Design, build, and operate AI-focused infrastructure platforms supporting model development, training, evaluation, and inference.
• Engineer scalable, reliable, and secure cloud-native services to support AI workloads across AWS, Azure, and hybrid environments.
• Partner with AI Engineering and Data Science teams to improve developer experience, performance, and operational stability of AI systems.
• Enable production deployment of ML models and LLMs within governed enterprise environments, aligned with firmwide risk and compliance standards.
• Implement and maintain infrastructure as code and automation to ensure repeatable, auditable platform provisioning.
• Build and operate observability, monitoring, and alerting solutions for AI platforms, ensuring availability, performance, and cost transparency.
• Collaborate with Security and Risk partners to integrate identity, access controls, data protection, and governance into AI infrastructure.
• Contribute to architectural decisions and technical standards for AI platforms across Aladdin.
• Participate in on-call rotations and operational support as required for critical platforms.
• Continuously evaluate emerging AI infrastructure technologies and apply them pragmatically within BlackRock’s enterprise context.

Qualifications

• Strong experience in cloud infrastructure, platform engineering, or systems engineering roles.
• 4+ hands-on expertise with AWS and/or Azure and/or GCP, including Azure ML, Azure Foundry, AWS Bedrock, Google Vertex, as well as cloud compute, networking, storage, and security services.
• Understanding of ML platform operations and governance concepts, including model deployment strategies, lifecycle management, monitoring/observability, and Disaster Recovery
• Experience supporting LLMs, generative AI platforms, or model serving infrastructure.
• Experience supporting AI and machine learning workloads, with exposure to managed compute for model training and fine-tuning, experimentation over large datasets, and end-to-end MLOps pipeline flow including data ingestion, training, validation, and deployment.
• Proficiency with Infrastructure as Code tools (e.g., Terraform, ARM/Bicep, CloudFormation).
• Strong programming or scripting skills (e.g., Python, Bash, or similar).
• Experience building and operating containerized and Kubernetes-based platforms.
• Solid understanding of reliability, scalability, observability, and operational best practices.
• Ability to work effectively in cross-functional teams and communicate complex technical concepts clearly.

Our Benefits

To help you stay energized, engaged, and inspired, we offer a wide range of employee benefits including: retirement investment and tools designed to help you in building a sound financial future; access to education reimbursement; comprehensive resources to support your physical health and emotional well-being; family support programs; and Flexible Time Off (FTO) so you can relax, recharge, and be there for the people you care about.

Our Hybrid Work Model

BlackRock’s hybrid work model is designed to enable a culture of collaboration and apprenticeship that enriches the experience of our employees, while supporting flexibility for all. Employees are currently required to work at least 4 days in the office per week, with the flexibility to work from home 1 day a week. Some business groups may require more time in the office due to their roles and responsibilities. We remain focused on increasing the impactful moments that arise when we work together in person – aligned with our commitment to performance and innovation. As a new joiner, you can count on this hybrid model to accelerate your learning and onboarding experience here at BlackRock.

XML job scraping automation by YubHub

Anthropic's mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.

About the Role

We are looking for a Threat Collections Engineer to join our Threat Intelligence team. In this role, you will build the infrastructure that powers our threat discovery capabilities—integrating external data sources, developing detection systems for automated lead generation, and creating internal tooling that scales our investigators' impact.

This is a foundational engineering role on a small, high-impact team. You will take projects from proof-of-concept to production, work closely with investigators to understand their needs, and help scale what may become a multi-person collections function.

Responsibilities:

• Build automated detection systems that use disparate signals to identify abusive behaviour.
• Take systems from idea to proof-of-concept to production-grade with appropriate monitoring, documentation, and maintenance processes
• Develop and maintain YARA rule infrastructure, including tools for writing, validating, and testing rules against real data
• Create integrations with external threat intelligence platforms (e.g. VirusTotal, Censys, Urlscan) via MCP servers to enable multi-source correlation during investigations
• Build data pipelines that ingest intelligence from RSS feeds, CTI news sources, and partner sharing, using Claude to extract TTPs and generate targeted hunting queries
• Develop behavioural analytics capabilities using DBT-based frameworks and create searchable audit logging infrastructure
• Establish feedback loops with investigators to tune detection systems and reduce false positives
• Scrape and normalise data from external sources to feed threat detection and enrichment workflows

You may be a good fit if you:

• Have strong coding proficiency in Python and SQL for building detection logic, data pipelines, and automation
• Have experience with data pipeline orchestration tools (Airflow, DBT, or similar)
• Have familiarity with threat intelligence concepts including IOCs, YARA rules, and threat correlation techniques
• Have experience integrating external APIs and building data ingestion systems
• Can translate investigator needs and workflows into technical requirements
• Are comfortable building v0 systems and iterating based on user feedback
• Have strong communication skills for working closely with non-engineering stakeholders

Strong candidates may also have:

• Experience with threat intelligence sharing frameworks (e.g. MISP, STIX/TAXII)
• Background in cyber threat intelligence, security operations, or abuse detection
• Experience building MCP servers or similar tool integrations for AI systems
• Familiarity with web scraping and data extraction at scale
• Experience with behavioural analytics or anomaly detection systems
• Understanding of LLM capabilities and how to leverage them for automation
• A Top Secret Clearance

Deadline to apply:

None. Applications will be reviewed on a rolling basis.

Logistics

Education requirements: We require at least a Bachelor's degree in a related field or equivalent experience. Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.

Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.

We encourage you to apply even if you do not believe you meet every single qualification.** Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team.

Your safety matters to us.** To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings.

How we're different

We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics as it does with computer science.

XML job scraping automation by YubHub