Dialpad is the AI-native business communications platform. We unify calling, messaging, meetings, and contact center on a single platform - powered by AI that understands every conversation in real time.

More than 70,000 companies around the globe, including WeWork, Asana, NASDAQ, AAA Insurance, COMPASS Realty, Uber, Randstad, and Tractor Supply, rely on Dialpad to build stronger customer connections using real-time, AI-driven insights.

We’re now leading the shift to Agentic AI: intelligent agents that don’t just analyze conversations but take action by automating workflows, resolving customer issues, and accelerating revenue in real time.

Our DAART initiative (Dialpad Agentic AI in Real Time) is redefining what a communications platform can do.

Visit dialpad.com to learn more.

Being a Dialer

At Dialpad, AI isn’t just a feature; it’s how our teams do their best work every day. We put powerful AI tools in every employee’s hands so they can move faster, think bigger, and achieve more.

We believe every conversation matters. And we’ve built the platform that turns those conversations into insight and action, for our customers and ourselves.

We look for people who are intensely curious and hold themselves to a high bar. Our ambition is significant, and achieving it requires a team that operates at the highest level.

We seek individuals who embody our core traits: Scrappy, Curious, Optimistic, Persistent, and Empathetic.

Your role

Dialpad’s Product Engineering organization is responsible for building and maintaining the customer-facing features at scale across all of our cloud-native products and services.

Every day, millions of users across the world leverage our technology for communicating effectively and efficiently.

Every engineer on our global engineering team is given the opportunity to take ownership of a large portion of the product where they’re able to see immediate results.

Combining natural language processing and artificial intelligence with world-class cloud computing, the things you’ll create at Dialpad will shape the future of work,enabling companies to work from anywhere and making business communication more human.

Dialpad’s Analytics team owns data pipelines, multiple databases, a modular query layer, and rich FE components to deliver intuitive and powerful end-user-facing analytics experiences that allow Dialpad customers to make data-driven business decisions.

Our teams are highly collaborative and comprise cross-disciplinary professionals, including Product Managers, Designers, QA specialists, as well as Engineers specialising in Data Engineering, Data Science, and Telephony.

This position reports to the Engineering Manager, who is based in Bengaluru, and the role will be based in our Bengaluru, India Office.

The position will require a hybrid working arrangement based out of our Bengaluru office.

What you’ll do

• Contribute to the design, development, and maintenance of information retrieval and distributed systems.

• Build and optimize search engines, including indexers, analyzers, ranking, and re-ranking strategies.

• Work on hybrid search techniques, including dense vector manipulation, rank fusion, and reranking.

• Maintain and enhance highly scalable search platforms with a focus on performance and cost efficiency.

• Ensure high availability, reliability, and fault tolerance in search services.

• Collaborate with cross-functional teams to translate business requirements into technical solutions.

• Develop and optimize real-time distributed systems, microservices, and message-driven architectures.

• Implement and maintain monitoring, alerting, and performance metrics for platform reliability.

• Evaluate and integrate emerging technologies to improve search capabilities.

• Write clean, modular, and well-tested code while following best engineering practices.

• Participate in code reviews to ensure quality, maintainability, and scalability.

• Provide mentorship and technical guidance to junior engineers.

Skills you’ll bring

• 4-7 years of experience in information retrieval or distributed systems engineering.

• Strong understanding of search platforms and experience maintaining search engines at scale.

• Deep knowledge of indexers, analyzers, field mapping, and ranking techniques.

• Experience with NLP/NLU within the context of information retrieval.

• Expertise in dense vector manipulation and optimization.

• Familiarity with hybrid search, rank fusion, and reranking techniques.

• Proficiency in Go and Python 3 (experience with Rust or TypeScript is a plus).

• Strong understanding of distributed systems, microservices, and message-driven architectures.

• Passion for real-time performance optimization and high availability.

• Experience with API design using Swagger, OpenAPI, or equivalent tools.

• Knowledge of gRPC or equivalent RPC protocols.

• Experience with Docker and Kubernetes for containerized deployments.

• Familiarity with cloud platforms (GCP preferred, AWS/Azure optional).

• Hands-on experience with Infrastructure as Code tools like Terraform or Ansible.

• Knowledge of CI/CD frameworks and continuous delivery practices.

Why Join Dialpad

• Work at the center of the AI transformation in business communications

• Build and ship agentic AI products that are redefining how companies operate

• Join a team where AI amplifies every employee’s impact

• Competitive salary, comprehensive benefits, and real opportunities for growth

We believe in investing in our people. Dialpad offers competitive benefits and perks, cutting-edge AI tools, and a robust training program that help you reach your full potential.

We have designed our offices to be inclusive, offering a vibrant environment to cultivate collaboration and connection.

Our exceptional culture, repeatedly recognized as a Great Place to Work, ensures that every employee feels valued and empowered to contribute to our collective success.

Don’t meet every single requirement? If you’re excited about this role and possess the fundamental traits, drive, and strong ambition we seek, but your experience doesn’t meet every qualification, we encourage you to apply.

Dialpad is an equal-opportunity employer. We are dedicated to creating a community of inclusion and an environment free from discrimination or harassment.

XML job scraping automation by YubHub

Location: Bengaluru, India

We're looking for a seasoned Director of Engineering to lead our data infrastructure organization in Bengaluru. As a founding technical leader in our fastest-growing engineering hub, you will be responsible for building world-class teams and shaping architectural decisions that ripple across the company.

About the Role:

• You will build the data infrastructure organization that makes Databricks' continued growth possible.
• Establish foundational teams in Bengaluru owning the bedrock systems that guarantee billing correctness, operational resilience, and zero-downtime recovery across our entire monetization stack.
• Define what world-class infrastructure looks like for the next decade of data platforms.

Responsibilities:

• Deliver the infrastructure vision for systems processing billions in daily billing transactions with zero tolerance for error.
• Build Bengaluru's data infrastructure organization by establishing it as the destination for India's top infrastructure talent.
• Own business-critical systems operating 24/7/365 across 100+ regions where even 99.9% uptime means hours of customer pain.
• Ship platforms that compound engineering leverage across Databricks.

Requirements:

• 14+ years in distributed systems engineering with 6+ years leading infrastructure organizations and 4+ years managing managers at companies where infrastructure failures meant immediate revenue impact, customer escalations, or regulatory consequences.
• Technical depth across petabyte-scale data pipelines and distributed systems reliability.
• Track record defining multi-year infrastructure vision and translating it into sequential deliverables that show value quarterly.
• Experience building 99.999%+ reliable systems with established practices for SLOs/SLIs, chaos engineering, disaster recovery, and sophisticated observability.
• Proven ability to scale infrastructure organizations in high-growth environments.
• Communication skills to make complex infrastructure decisions legible to executives.

What You'll Need:

• BS in Computer Science or Engineering; MS or Ph.D. preferred.
• Experience with Apache Spark, Delta Lake, large-scale data infrastructure, fintech/billing systems, or leading infrastructure through hypergrowth strongly preferred.

Benefits:

At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees.

Our Commitment to Diversity and Inclusion:

At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel.

Compliance:

If access to export-controlled technology or source code is required for performance of job duties, it is within Employer's discretion whether to grant such access.

XML job scraping automation by YubHub

In this leadership opportunity, you will build the data infrastructure organization that makes Databricks' continued growth possible. You'll establish foundational teams in Bengaluru owning the bedrock systems that guarantee billing correctness, operational resilience, and zero-downtime recovery across our entire monetization stack, alongside multi-region data ingestion, developer platforms, and deployment automation that eliminate friction at petabyte scale.

This isn't about maintaining what exists; it's about architecting the infrastructure that enables Databricks to scale while reducing operational burden. You'll define what world-class infrastructure looks like for the next decade of data platforms.

The impact you'll have:

• Deliver the infrastructure vision for systems processing billions in daily billing transactions with zero tolerance for error, building disaster recovery that's provably reliable, testing frameworks that catch what production sees, correctness systems that make billing errors structurally impossible, and observability that predicts failures before they happen

• Build Bengaluru's data infrastructure organization by establishing it as the destination for India's top infrastructure talent, hiring multiple engineering managers who become force multipliers, and creating a culture where solving hard distributed systems problems at scale is the daily work

• Own business-critical systems operating 24/7/365 across 100+ regions where even 99.9% uptime means hours of customer pain, driving reliability improvements that prevent millions in revenue loss while eliminating operational toil through frameworks that make systems self-healing, self-tuning, and self-documenting

• Ship platforms that compound engineering leverage across Databricks: correctness frameworks that catch billing errors before customers do, deployment automation that makes regional expansion push-button, data integration systems that process petabyte-scale flows without human intervention, and testing infrastructure where comprehensive coverage is automatic, not heroic

• Position infrastructure as product by treating internal engineering teams as customers with SLAs, measuring adoption and satisfaction, iterating based on feedback, and demonstrating that every dollar invested in infrastructure returns multiplicative gains in product velocity, reliability improvements, or cost reductions

You'll need:

• 14+ years in distributed systems engineering with 6+ years leading infrastructure organizations and 4+ years managing managers at companies where infrastructure failures meant immediate revenue impact, customer escalations, or regulatory consequences - and you built the systems and teams that made those failures rare

• Technical depth across petabyte-scale data pipelines and distributed systems reliability where you can engage from 'how should we architect multi-region disaster recovery' to 'why is this Kafka cluster exhibiting this latency pattern' while knowing when to coach versus when to decide

• Track record defining multi-year infrastructure vision and translating it into sequential deliverables that show value quarterly while building toward architectural end states, positioning infrastructure investments as business enablers rather than cost centers, and making build-vs-buy decisions that compound over time

• Experience building 99.999%+ reliable systems with established practices for SLOs/SLIs, chaos engineering, disaster recovery, and sophisticated observability that predicts failures before they happen

• Proven ability to scale infrastructure organizations in high-growth environments where you've doubled engineering while maintaining quality bar, developed engineering managers, and created teams where retention is high because the problems are interesting and the culture is strong

• Communication skills to make complex infrastructure decisions legible to executives (translating technical investments into business outcomes), influence cross-functional partners without authority, build trust across global teams in different timezones with different working styles, and represent Databricks' technical brand externally

BS in Computer Science or Engineering; MS or Ph.D. preferred. Experience with Apache Spark, Delta Lake, large-scale data infrastructure, fintech/billing systems, or leading infrastructure through hypergrowth strongly preferred.

XML job scraping automation by YubHub

Your responsibilities will include:

• Designing and building distributed systems that process, enrich, and respond to billions of behavioral events per day in real time
• Developing high-performance APIs and services that support advertising, identity, and intent features across the Marketing Platform
• Leveraging machine learning and large language models (LLMs) to analyze behavioral data, classify content, extract signals, and enable intelligent decision-making
• Building intelligent agents using frameworks like LangGraph or MCP to reason over data and power user-facing insights
• Designing and operating data pipelines using tools like Kafka, Kinesis, and ClickHouse to support both streaming and batch workloads
• Driving quality, performance, scalability, and observability across all systems you own
• Collaborating cross-functionally with product managers, data scientists, and engineers to deliver customer-facing features and internal tooling
• Contributing to technical leadership and mentorship of teammates

We're looking for someone with 8+ years of backend, data, or infrastructure engineering experience, or equivalent impact and leadership. You should have strong experience in at least one of the following areas:

• Distributed systems engineering
• Big data infrastructure
• Applied AI/ML

You should also be proficient in one or more core languages (Java, Go, Python), have a solid grasp of SQL and large-scale data modeling, and familiarity with databases and tools such as ClickHouse, DynamoDB, Bigtable, Memcached, Kafka, Kinesis, Firehose, Airflow, Snowflake.

Bonus points if you have experience in ad tech, real-time bidding (RTB), or programmatic systems, background in identity resolution, attribution, or behavioral analytics at scale, contributions to open source in ML, infrastructure, or data tooling, or strong product instincts and a passion for building tools that drive meaningful outcomes.

XML job scraping automation by YubHub

Location

San Francisco

Employment Type

Full time

Department

Scaling

Compensation

• $310K – $460K • Offers Equity

The base pay offered may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. If the role is non-exempt, overtime pay will be provided consistent with applicable laws. In addition to the salary range listed above, total compensation also includes generous equity, performance-related bonus(es) for eligible employees, and the following benefits.

• Medical, dental, and vision insurance for you and your family, with employer contributions to Health Savings Accounts

• Pre-tax accounts for Health FSA, Dependent Care FSA, and commuter expenses (parking and transit)

• 401(k) retirement plan with employer match

• Paid parental leave (up to 24 weeks for birth parents and 20 weeks for non-birthing parents), plus paid medical and caregiver leave (up to 8 weeks)

• Paid time off: flexible PTO for exempt employees and up to 15 days annually for non-exempt employees

• 13+ paid company holidays, and multiple paid coordinated company office closures throughout the year for focus and recharge, plus paid sick or safe time (1 hour per 30 hours worked, or more, as required by applicable state or local law)

• Mental health and wellness support

• Employer-paid basic life and disability coverage

• Annual learning and development stipend to fuel your professional growth

• Daily meals in our offices, and meal delivery credits as eligible

• Relocation support for eligible employees

• Additional taxable fringe benefits, such as charitable donation matching and wellness stipends, may also be provided.

More details about our benefits are available to candidates during the hiring process.

This role is at-will and OpenAI reserves the right to modify base pay and other compensation components at any time based on individual performance, team or company results, or market conditions.

About the Team

The Platform Systems team at OpenAI operates at the intersection of cutting-edge AI and large-scale distributed systems. We build the engineering and research infrastructure required to train OpenAI’s flagship models on some of the world’s largest, custom-built supercomputers.

Our team develops core model training software and works deep in the stack - spanning collective communication, compute efficiency, parallelism strategies, fault tolerance, failure detection, and observability. The systems we build are foundational to OpenAI’s research velocity, enabling reliable, efficient training at frontier scale.

We collaborate closely with researchers across the organization, continuously incorporating learnings from across OpenAI into the evolution of our training platform.

About the Role

As a Software Engineer, Platform Systems, you will design and build distributed systems that provide visibility into large-scale training workloads and help operate them reliably at scale.

You’ll work on failure detection, tracing, and observability systems that identify slow or faulty nodes, surface performance bottlenecks, and help engineers understand and optimize massive distributed training jobs. This infrastructure is critical to operating OpenAI’s training stack and is actively evolving to support new use cases and increasingly complex workloads.

This role sits at the core of our training infrastructure, blending systems engineering, performance analysis, and large-scale debugging.

In This Role, You Will

• Design and build distributed failure detection, tracing, and profiling systems for large-scale AI training jobs

• Develop tooling to identify slow, faulty, or misbehaving nodes and provide actionable visibility into system behavior

• Improve observability, reliability, and performance across OpenAI’s training platform

• Debug and resolve issues in complex, high-throughput distributed systems

• Collaborate with systems, infrastructure, and research teams to evolve platform capabilities

• Extend and adapt failure detection systems or tracing systems to support new training paradigms and workloads

You Might Thrive in This Role If You

• Care deeply about performance, stability, and observability in distributed systems

• Enjoy finding and fixing issues in large-scale systems and automating operational workflows

• Have experience writing low-level software where system details matter

• Understand hardware, operating systems, networking, concurrency, and distributed systems

• Have a background in high-performance computing or low-level systems engineering

• Are excited to work on critical infrastructure that powers frontier AI research

About OpenAI

OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity.

XML job scraping automation by YubHub

Location

San Francisco

Employment Type

Full time

Department

Scaling

Compensation

• $230K – $490K • Offers Equity

The base pay offered may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. If the role is non-exempt, overtime pay will be provided consistent with applicable laws. In addition to the salary range listed above, total compensation also includes generous equity, performance-related bonus(es) for eligible employees, and the following benefits.

• Medical, dental, and vision insurance for you and your family, with employer contributions to Health Savings Accounts

• Pre-tax accounts for Health FSA, Dependent Care FSA, and commuter expenses (parking and transit)

• 401(k) retirement plan with employer match

• Paid parental leave (up to 24 weeks for birth parents and 20 weeks for non-birthing parents), plus paid medical and caregiver leave (up to 8 weeks)

• Paid time off: flexible PTO for exempt employees and up to 15 days annually for non-exempt employees

• 13+ paid company holidays, and multiple paid coordinated company office closures throughout the year for focus and recharge, plus paid sick or safe time (1 hour per 30 hours worked, or more, as required by applicable state or local law)

• Mental health and wellness support

• Employer-paid basic life and disability coverage

• Annual learning and development stipend to fuel your professional growth

• Daily meals in our offices, and meal delivery credits as eligible

• Relocation support for eligible employees

• Additional taxable fringe benefits, such as charitable donation matching and wellness stipends, may also be provided.

More details about our benefits are available to candidates during the hiring process.

This role is at-will and OpenAI reserves the right to modify base pay and other compensation components at any time based on individual performance, team or company results, or market conditions.

About the Team

The Frontier Systems team at OpenAI builds, launches, and supports the largest supercomputers in the world that OpenAI uses for its most cutting edge model training.

We take data center designs, turn them into real, working systems and build any software needed for running large-scale frontier model trainings.

Our mission is to bring up, stabilize and keep these hyperscale supercomputers reliable and efficient during the training of the frontier models.

About the Role

We are looking for engineers to operate the next generation of compute clusters that power OpenAI’s frontier research.

This role blends distributed systems engineering with hands-on infrastructure work on our largest datacenters. You will scale Kubernetes clusters to massive scale, automate bare-metal bring-up, and build the software layer that hides the complexity of a magnitude of nodes across multiple data centers.

You will work at the intersection of hardware and software, where speed and reliability are critical. Expect to manage fast-moving operations, quickly diagnose and fix issues when things are on fire, and continuously raise the bar for automation and uptime.

In this role, you will:

• Spin up and scale large Kubernetes clusters, including automation for provisioning, bootstrapping, and cluster lifecycle management

• Build software abstractions that unify multiple clusters and present a seamless interface to training workloads

• Own node bring-up from bare metal through firmware upgrades, ensuring fast, repeatable deployment at massive scale

• Improve operational metrics such as reducing cluster restart times (e.g., from hours to minutes) and accelerating firmware or OS upgrade cycles

• Integrate networking and hardware health systems to deliver end-to-end reliability across servers, switches, and data center infrastructure

• Develop monitoring and observability systems to detect issues early and keep clusters stable under extreme load

You might thrive in this role if you:

• Have deep experience operating or scaling Kubernetes clusters or similar container orchestration systems in high-growth or hyperscale environments

• Bring strong programming or scripting skills (Python, Go, or similar) and familiarity with Infrastructure-as-Code tools such as Terraform or CloudFormation

• Are comfortable with bare-metal Linux environments, GPU hardware, and large-scale networking

• Enjoy solving fast-moving, high-impact operational problems and building automation to eliminate manual work

• Can balance careful engineering with the urgency of keeping mission-critical systems running

Qualifications

• Experience as an infrastructure, systems, or distributed systems engineer in large-scale or high-availability environments

• Strong knowledge of Kubernetes internals, cluster scaling patterns, and containerized workloads

• Proficiency in cloud infrastructure concepts (compute, networking, storage, security) and in automating cluster or data center operations

_Bonus: background with GPU workloads, firmware management, or high-performance computing_

About OpenAI

OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity.

XML job scraping automation by YubHub

Location

San Francisco

Employment Type

Full time

Department

Scaling

Compensation

• $255K – $490K • Offers Equity

The base pay offered may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. If the role is non-exempt, overtime pay will be provided consistent with applicable laws. In addition to the salary range listed above, total compensation also includes generous equity, performance-related bonus(es) for eligible employees, and the following benefits.

• Medical, dental, and vision insurance for you and your family, with employer contributions to Health Savings Accounts

• Pre-tax accounts for Health FSA, Dependent Care FSA, and commuter expenses (parking and transit)

• 401(k) retirement plan with employer match

• Paid parental leave (up to 24 weeks for birth parents and 20 weeks for non-birthing parents), plus paid medical and caregiver leave (up to 8 weeks)

• Paid time off: flexible PTO for exempt employees and up to 15 days annually for non-exempt employees

• 13+ paid company holidays, and multiple paid coordinated company office closures throughout the year for focus and recharge, plus paid sick or safe time (1 hour per 30 hours worked, or more, as required by applicable state or local law)

• Mental health and wellness support

• Employer-paid basic life and disability coverage

• Annual learning and development stipend to fuel your professional growth

• Daily meals in our offices, and meal delivery credits as eligible

• Relocation support for eligible employees

• Additional taxable fringe benefits, such as charitable donation matching and wellness stipends, may also be provided.

More details about our benefits are available to candidates during the hiring process.

This role is at-will and OpenAI reserves the right to modify base pay and other compensation components at any time based on individual performance, team or company results, or market conditions.

About the Team

The Frontier Systems team at OpenAI builds, launches, and supports the largest supercomputers in the world that OpenAI uses for its most cutting edge model training.

We take data center designs, turn them into real, working systems and build any software needed for running large-scale frontier model trainings.

Our mission is to bring up, stabilize and keep these hyperscale supercomputers reliable and efficient during the training of the frontier models.

About the Role

We are looking for engineers to operate the next generation of compute clusters that power OpenAI’s frontier research.

This role blends distributed systems engineering with hands-on infrastructure work on our largest datacenters. You will scale Kubernetes clusters to massive scale, automate bare-metal bring-up, and build the software layer that hides the complexity of a magnitude of nodes across multiple data centers.

You will work at the intersection of hardware and software, where speed and reliability are critical. Expect to manage fast-moving operations, quickly diagnose and fix issues when things are on fire, and continuously raise the bar for automation and uptime.

In this role, you will:

• Spin up and scale large Kubernetes clusters, including automation for provisioning, bootstrapping, and cluster lifecycle management

• Build software abstractions that unify multiple clusters and present a seamless interface to training workloads

• Own node bring-up from bare metal through firmware upgrades, ensuring fast, repeatable deployment at massive scale

• Improve operational metrics such as reducing cluster restart times (e.g., from hours to minutes) and accelerating firmware or OS upgrade cycles

• Integrate networking and hardware health systems to deliver end-to-end reliability across servers, switches, and data center infrastructure

• Develop monitoring and observability systems to detect issues early and keep clusters stable under extreme load

• Be expected to execute at the same level as a software engineer

You might thrive in this role if you:

• Have deep experience operating or scaling Kubernetes clusters or similar container orchestration systems in high-growth or hyperscale environments

• Bring strong programming or scripting skills (Python, Go, or similar) and familiarity with Infrastructure-as-Code tools such as Terraform or CloudFormation

• Are comfortable with bare-metal Linux environments, GPU hardware, and large-scale networking

• Enjoy solving fast-moving, high-impact operational problems and building automation to eliminate manual work

• Can balance careful engineering with the urgency of keeping mission-critical systems running

Qualifications

• Experience as an infrastructure, systems, or distributed systems engineer in large-scale or high-availability environments

• Strong knowledge of Kubernetes internals, cluster scaling patterns, and containerized workloads

• Proficiency in cloud infrastructure concepts (compute, networking, storage, security) and in automating cluster or data center operations

_Bonus: background with GPU workloads, firmware management, or high-performance computing_

XML job scraping automation by YubHub

Location

London, UK

Employment Type

Full time

Department

Scaling

About the Team

The Platform Systems team at OpenAI operates at the intersection of cutting-edge AI and large-scale distributed systems. We build the engineering and research infrastructure required to train OpenAI’s flagship models on some of the world’s largest, custom-built supercomputers.

Our team develops core model training software and works deep in the stack - spanning collective communication, compute efficiency, parallelism strategies, fault tolerance, failure detection, and observability. The systems we build are foundational to OpenAI’s research velocity, enabling reliable, efficient training at frontier scale.

We collaborate closely with researchers across the organisation, continuously incorporating learnings from across OpenAI into the evolution of our training platform.

About the Role

As a Software Engineer, Platform Systems, you will design and build distributed systems that provide visibility into large-scale training workloads and help operate them reliably at scale.

You’ll work on failure detection, tracing, and observability systems that identify slow or faulty nodes, surface performance bottlenecks, and help engineers understand and optimise massive distributed training jobs. This infrastructure is critical to operating OpenAI’s training stack and is actively evolving to support new use cases and increasingly complex workloads.

This role sits at the core of our training infrastructure, blending systems engineering, performance analysis, and large-scale debugging.

In This Role, You Will

• Design and build distributed failure detection, tracing, and profiling systems for large-scale AI training jobs

• Develop tooling to identify slow, faulty, or misbehaving nodes and provide actionable visibility into system behaviour

• Improve observability, reliability, and performance across OpenAI’s training platform

• Debug and resolve issues in complex, high-throughput distributed systems

• Collaborate with systems, infrastructure, and research teams to evolve platform capabilities

• Extend and adapt failure detection systems or tracing systems to support new training paradigms and workloads

You Might Thrive in This Role If You

• Care deeply about performance, stability, and observability in distributed systems

• Enjoy finding and fixing issues in large-scale systems and automating operational workflows

• Have experience writing low-level software where system details matter

• Understand hardware, operating systems, networking, concurrency, and distributed systems

• Have a background in high-performance computing or low-level systems engineering

• Are excited to work on critical infrastructure that powers frontier AI research

About OpenAI

OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity.

XML job scraping automation by YubHub

Microsoft are looking for a talented Principal Software Engineer at their Bengaluru office. This role sits at the heart of strategic decision-making, turning market data into actionable insights for a company that's revolutionising AI technology. You'll work directly with leadership to shape the company's direction in the AI market.

About the Role

We are looking for a Principal Software Engineer who is hands-on with production coding and system design to build the real-time data pipelines and feature/embedding materialization systems that feed online stores/caches and integrate tightly with ML inference serving. This role is ideal for engineers who enjoy building robust streaming + ETL systems (correctness, idempotency, backfills, late data), owning SLOs with strong observability and operational maturity, and optimizing end-to-end performance and cost across compute, storage, and serving integrations.

Accountabilities

• Design and implement real-time streaming ETL / feature pipelines (e.g., Flink or Spark Structured Streaming) that meet strict freshness and correctness constraints.
• Build and operate reliable messaging and ingestion with Kafka/Pulsar (partitioning strategy, retries, ordering guarantees, DLQs, backpressure handling).

The Candidate we're looking for

Experience:

• Bachelor’s or Master’s degree in Computer Science, Electrical/Computer Engineering, or a related field, with 8+ years of related experience.

Technical skills:

• Strong programming skills in language C++, C# or Python (at least one required).
• Hands-on experience in one or more: Building and operating streaming data pipelines in production (Flink or Spark Structured Streaming), Distributed systems engineering with strong reliability and operational rigor, Messaging systems such as Kafka/Pulsar.

Personal attributes:

• Strong communication and collaboration skills, with experience working across engineering, applied science/ML, and product/business stakeholders.

Benefits

• Competitive salary and benefits package.
• Opportunities for professional growth and development.
• Collaborative and dynamic work environment.

XML job scraping automation by YubHub