Your responsibilities will include:

• Designing extensible, production-grade services that can support frontier AI workflows, including multi-modal inputs, long-running processes, and agentic orchestration.
• Building and operating distributed systems at scale, with strong guarantees around correctness, reliability, observability, and cost efficiency.
• Integrating with public LLM APIs and AI services, designing abstractions that are resilient to model churn, latency variability, and evolving usage patterns.
• Designing and maintaining data transformation and processing systems, supporting complex schema evolution, customization, and high-throughput workloads.
• Partnering closely with infrastructure, product, and customer-facing teams to define requirements, shape technical direction, and deliver seamless integration experiences for customers.
• Leading multi-quarter technical initiatives, including authoring and driving a 6+ month technical roadmap for major platform investments.
• Applying strong engineering judgment in ambiguous problem spaces, balancing speed with long-term maintainability and operational excellence.
• Raising the quality bar through thoughtful system design reviews, rigorous code reviews, and mentorship grounded in real-world production experience.

Ideal Experience:

• 7+ years of professional software engineering experience, with a strong background in building and operating large-scale, production-grade platforms.
• Deep expertise in distributed systems and cloud-native architectures, including Kubernetes, microservices, event-driven systems, caching, and production databases.
• Proven ability to lead multi-quarter technical initiatives, work effectively across cross-functional teams, and apply strong architectural judgment in ambiguous environments.

Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position, determined by work location and additional factors, including job-related skills, experience, interview performance, and relevant education or training.

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Responsibilities:

• Design, implement, and maintain reliable and horizontally scalable distributed systems
• Work closely with the team to identify and solve pain points
• Collaborate with the team to ensure high-quality code and architecture
• Participate in code reviews and contribute to the improvement of the codebase

Requirements:

• Expert knowledge of either Rust or C++
• Experience in designing, implementing, and maintaining reliable and horizontally scalable distributed systems
• Knowledge of service observability and reliability best practices
• Experience in operating commonly used databases such as PostgreSQL, Clickhouse, and MongoDB

Preferred Skills and Experience:

• Knowledge of Python
• Experience with Docker, Kubernetes, and containerized applications
• Expert knowledge of gRPC (unary, response streaming, bi-directional streaming, REST mapping)
• Hands-on experience with LLM APIs, embeddings, or RAG patterns
• Track record of delivering user-facing software at scale

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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 analyse 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 --------------- 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 -------- As a Sr. SDET in Agentic QA, you will own the test automation and quality frameworks that support Dialpad’s AI Voice Agent services.

You will develop automated tests for end-to-end product experiences, from frontend UI to backend services to APIs to audio/text interactions.

You will test orchestration flows, agent configuration experiences, and guardian safeguards to create robust automated coverage for functionality, performance, reliability, UX, and more.

In this role, you will develop substantial amounts of automated test infrastructure and partner deeply with the development team to make our fast-growing AI platform more testable, more stable, and more delightful for customers.

This position is based at one of Dialpad’s Canadian offices and reports to a QA Eng Manager in the United States.

What you’ll do ------------

• Own end-to-end quality for agentic features and workflows, including strategy, development, execution, and release qualification.
• Design and build automation tooling and frameworks for AI/LLM-driven systems, including prompt flows, agent orchestration, and tool integrations.
• Develop and maintain evaluation frameworks (evals) to measure response quality, accuracy, and hallucination rates.
• Drive automation coverage (80%+ for critical AI workflows) using deterministic + probabilistic validation approaches.
• Integrate AI quality checks into CI/CD pipelines with fast feedback cycles (
• Build tooling for LLM observability and debugging, including prompt tracing and response analysis.
• Partner with Applied AI teams on prompt engineering, model selection, and evaluation strategies.
• Design and execute performance and load tests for AI services (latency, throughput, cost efficiency).
• Identify and mitigate risks related to hallucinations, bias, safety, and edge cases.
• Define and track AI quality KPIs (task success rates, precision/recall, latency, etc.).
• Participate in design and architecture reviews to ensure systems are testable, observable, and resilient.
• Mentor engineers and contribute to raising the bar on AI quality engineering practices.

What you’ll bring --------------

• 5+ years of experience in software engineering or SDET roles with an emphasis on software development.
• Strong programming skills in Python (preferred), Java, or JavaScript.
• Experience testing distributed, cloud-native SaaS systems and APIs.
• Demonstrated proficiency in coding with AI agents to accelerate development and improve code quality.
• Hands-on exposure to LLMs or AI/ML systems (e.g., OpenAI, Claude, Gemini, or similar platforms).
• Understanding of non-deterministic systems and probabilistic testing approaches.
• Experience building test frameworks and scalable automation systems.
• Familiarity with AI evaluation techniques (benchmarking, golden datasets, human-in-the-loop validation).
• Experience with CI/CD pipelines (e.g., Jenkins, GitHub Actions).
• Strong collaboration skills with the ability to work across distributed teams and time zones.
• Bachelor’s degree in Computer Science or equivalent practical experience.

Backend: Python, Go, Google Cloud Platform, Cloud Run / App Engine, Kubernetes, Datastore, Redis, ElasticSearch.

• Frontend: Vue3, React.
• AI Stack: LLM APIs, LiveKit, prompt orchestration frameworks, evaluation tooling.

For exceptional talent based in British Columbia, Canada the target base salary range for this position is $150,500-$175,250 CAD.

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.

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Responsibilities:

• Design, implement, and maintain reliable and horizontally scalable distributed systems
• Develop expertise in service observability and reliability best practices
• Operate commonly used databases such as PostgreSQL, Clickhouse, and CockroachDB
• Work hand-in-hand with customers to gather feedback, refine features, and evolve products to address real-world challenges

Requirements:

• Expert knowledge of either Rust or C++
• Experience in designing, implementing, and maintaining reliable and horizontally scalable distributed systems
• Knowledge of service observability and reliability best practices
• Experience in operating commonly used databases such as PostgreSQL, Clickhouse, and CockroachDB

Preferred Skills and Experience:

• Expert knowledge of Python
• Experience with Docker, Kubernetes, and containerized applications
• Expert knowledge of TypeScript
• Expert knowledge of gRPC (unary, response streaming, bi-directional streaming, REST mapping)
• Hands-on experience with LLM APIs, embeddings, or RAG patterns
• Track record of delivering user-facing software at scale

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We're looking for a skilled Backend Engineer to join our team at xAI. As a Backend Engineer, you will work on our production systems that power the API.

About xAI:

xAI's mission is to create AI systems that can accurately understand the universe and aid humanity in its pursuit of knowledge. Our team is small, highly motivated, and focused on engineering excellence.

Responsibilities:

• Work on xAI's production systems that power the API
• Design, implement, and maintain reliable and horizontally scalable distributed systems
• Operate commonly used databases such as PostgreSQL, Clickhouse, and MongoDB
• Ensure service observability and reliability best practices

Requirements:

• Expert knowledge of either Rust or C++
• Experience in designing, implementing, and maintaining reliable and horizontally scalable distributed systems
• Knowledge of service observability and reliability best practices
• Experience in operating commonly used databases such as PostgreSQL, Clickhouse, and MongoDB

Preferred Skills and Experience:

• Knowledge of Python
• Experience with Docker, Kubernetes, and containerized applications
• Expert knowledge of gRPC (unary, response streaming, bi-directional streaming, REST mapping)
• Hands-on experience with LLM APIs, embeddings, or RAG patterns
• Track record of delivering user-facing software at scale

Benefits:

• Strong communication skills
• Ability to concisely and accurately share knowledge with teammates
• Flat organisational structure
• Opportunity to work on challenging projects

Note: This job description is a rewritten version of the original ad, focusing on the job requirements and responsibilities.

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You'll own our full GTM tech stack including Salesforce, Outreach, Gong, Apollo, Clay, Claude, and more, and be responsible for how we use AI to transform the way our field teams work. This is a high-visibility, high-ownership role that sits at the intersection of revenue strategy and technical execution.

Responsibilities:

• Identify, build, and iterate on AI-powered workflows using Hebbia, Claude, Clay, and adjacent tools for both pre- and post-sales teams
• Build and maintain prompt libraries and role-specific AI assistants that give field team members leverage in their day-to-day work; set up measurement frameworks to track what's actually moving the needle
• Own, administer, and continuously improve our core GTM tools, serving as the internal subject matter expert for each
• Keep all systems integrated and healthy, with clean data flowing across the stack so that every downstream workflow, report, and automation is built on a foundation that can be trusted
• Audit the full GTM workflow for manual, repetitive work and systematically replace it with automation across data capture, field updates, handoffs, lead enrichment, sequence enrollment, and signal monitoring
• Work closely with GTM and Operations to understand pain points, translate problems into technical solutions, and rollout processes and workflows

Requirements:

• 4 to 7 years of experience in Revenue Operations, GTM Systems, GTM Engineering, or a closely adjacent technical role in a B2B SaaS environment
• Practical experience with prompt engineering and building AI-assisted workflows using LLM APIs or tools like Claude
• Deep hands-on experience with GTM tools including Salesforce, Gong, Outreach, Apollo, and Clay, with a track record of building workflows and automations that teams actually use
• Comfortable working directly with APIs, webhooks, and data integrations. You can connect systems and debug sync issues without filing an engineering ticket
• Experience owning vendor relationships including renewals, evaluations, and contract negotiations
• Experience in fast-paced environments and be comfortable working both as part of a team and independently
• Demonstrated ability to prioritize workload and manage multiple concurrent projects
• Strong verbal and written communication skills; ability to work effectively with cross-functional teams

Total cash compensation range for this role is $140,000 to $190,000.

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You'll own our full GTM tech stack including Salesforce, Outreach, Gong, Apollo, Clay, Claude, and more, and be responsible for how we use AI to transform the way our field teams work. This is a high-visibility, high-ownership role that sits at the intersection of revenue strategy and technical execution.

Responsibilities:

• Identify, build, and iterate on AI-powered workflows using Hebbia, Claude, Clay, and adjacent tools for both pre- and post-sales teams
• Build and maintain prompt libraries and role-specific AI assistants that give field team members leverage in their day-to-day work; set up measurement frameworks to track what's actually moving the needle
• Own, administer, and continuously improve our core GTM tools, serving as the internal subject matter expert for each
• Keep all systems integrated and healthy, with clean data flowing across the stack so that every downstream workflow, report, and automation is built on a foundation that can be trusted
• Audit the full GTM workflow for manual, repetitive work and systematically replace it with automation across data capture, field updates, handoffs, lead enrichment, sequence enrollment, and signal monitoring

Cross-Functional Partnership:

• Work closely with the GTM and Operations teams to understand pain points, translate problems into technical solutions, and rollout processes and workflows

Who You Are:

• 4 to 7 years of experience in Revenue Operations, GTM Systems, GTM Engineering, or a closely adjacent technical role in a B2B SaaS environment
• Practical experience with prompt engineering and building AI-assisted workflows using LLM APIs or tools like Claude
• Deep hands-on experience with GTM tools including Salesforce, Gong, Outreach, Apollo, and Clay, with a track record of building workflows and automations that teams actually use
• Comfortable working directly with APIs, webhooks, and data integrations. You can connect systems and debug sync issues without filing an engineering ticket
• Experience owning vendor relationships including renewals, evaluations, and contract negotiations
• Experience in fast-paced environments and be comfortable working both as part of a team and independently
• Demonstrated ability to prioritize workload and manage multiple concurrent projects
• Strong verbal and written communication skills; ability to work effectively with cross-functional teams

Compensation:

• The total cash compensation range for this role is $140,000 to $190,000. This range may be inclusive of several career levels at Hebbia and will be narrowed during the interview process based on the candidate’s experience and qualifications. Adjustments outside of this range may be considered for candidates whose qualifications significantly differ from those outlined in the job description.

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As a Senior Product Manager, you will work at the nexus of product and research, driving execution in partnership with engineers, language engineers, data scientists and researchers. You will develop and execute on LLM platform strategy for Copilot that extend language model's capabilities. You will prototype approaches by steering language models to drive response quality across a wide range of scenarios. You will identify and prioritise platform, orchestration and language model issues that impact quality, factuality and safety and working with engineers and researchers to find a path to resolution.

You will define and build measurable evaluations with relevant datasets to demonstrate quality improvements. You will define, deploy and manage experiments in production that impact language model's tool use, driving measurable improvements in relevance for and engagement with Copilot users. You will partner with product teams to scale tool building and work with inference, agents and orchestration teams to resolve dependencies. You will be accountable to own the status of key projects, proactively identifying risks and proposing solutions to ensure timely delivery.

Responsibilities include:

• Developing and executing on LLM platform strategy for Copilot that extend language model's capabilities
• Prototyping approaches by steering language models to drive response quality across a wide range of scenarios
• Identifying and prioritising platform, orchestration and language model issues that impact quality, factuality and safety and working with engineers and researchers to find a path to resolution
• Defining and building measurable evaluations with relevant datasets to demonstrate quality improvements
• Defining, deploying and managing experiments in production that impact language model's tool use, driving measurable improvements in relevance for and engagement with Copilot users
• Partnering with product teams to scale tool building and working with inference, agents and orchestration teams to resolve dependencies
• Being accountable to own the status of key projects, proactively identifying risks and proposing solutions to ensure timely delivery

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Microsoft AI are looking for a talented Senior Product Manager, Copilot AI at their Mountain View 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 landscape.

About the Role

As a Senior Product Manager, you will drive Copilot model capabilities such as tool-use to ensure that the language models that power Microsoft Copilot deliver high quality responses to our users whilst being grounded, reliable, and cost-efficient. You will work at the nexus of product and research, driving execution in partnership with engineers, language engineers, data scientists and researchers.

Accountabilities

• Develop and execute on LLM platform strategy for Copilot that extend language model’s capabilities.
• Prototype approaches by steering language models to drive response quality across a wide range of scenarios.

The Candidate we're looking for

Experience:

• 5+ years experience in product management.
• 3+ years of experience leading ambiguous product areas, defining requirements, developing roadmaps, and working with multi-disciplinary teams to execute them.

Technical skills:

• Hands-on experience with LLM APIs (e.g. OpenAI, Anthropic, Azure OpenAI), embeddings, vector databases, and tool use.
• Hands-on experience with prompt design, context window management, and model evaluation.

Personal attributes:

• Abundance of positive energy, empathy, and kindness.
• Highly effective.

Benefits

• Competitive salary.
• Benefits and other compensation.

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