Production Automation Developer Jobs

About the Team The Applied AI Engineering team is responsible for helping developers and enterprises safely and effectively deploy OpenAI technologies in production. We act as trusted technical advisors and thought partners for customers, working side by side with their teams to identify high-value use cases, design practical architectures, and move from prototype to durable deployment. Cybersecurity is one of the most urgent domains where AI can help. Security teams are under pressure to reason across code, logs, infrastructure, tickets, alerts, and vulnerability data faster than ever. As frontier models become more capable, organizations need deep technical guidance on how to evaluate, validate, and safely deploy AI systems in security-critical workflows. About the Role We are looking for an Applied AI Engineer, Cyber to partner with customers and help them apply OpenAI models, APIs, Codex, and agentic workflows to real cybersecurity use cases. You will work with CISOs, security executives, application security leaders, SOC teams, security engineering teams, and hands-on practitioners to identify where AI can create measurable security outcomes. This is a customer-facing technical role for someone who can move fluidly between executive strategy, practitioner-level cyber depth, and hands-on solution design. You will help customers evaluate and deploy workflows such as secure code review, vulnerability triage, threat modeling, remediation, SOC and incident response workflows, detection engineering, cloud security, GRC automation, and security validation. You will collaborate closely with Sales, Solutions Engineering, Product, Engineering, Research, and Security to turn customer needs into safe deployment patterns, reusable field assets, and product feedback. This role is based in our Singapore office. We offer relocation support to new employees. In this role, you will: Deeply embed with strategic customers as the technical lead for AI-enabled cybersecurity workflow

About the team The Applied AI Engineering team is responsible for helping developers and enterprises safely and effectively deploy OpenAI technologies in production. We act as trusted technical advisors and thought partners for customers, working side by side with their teams to identify high-value use cases, design practical architectures, and move from prototype to durable deployment. Cybersecurity is one of the most urgent domains where AI can help. Security teams are under pressure to reason across code, logs, infrastructure, tickets, alerts, and vulnerability data faster than ever. As frontier models become more capable, organizations need deep technical guidance on how to evaluate, validate, and safely deploy AI systems in security-critical workflows. About the role We are looking for a Cybersecurity Applied AI Engineer to partner with customers and help them apply OpenAI models, APIs, Codex, and agentic workflows to real cybersecurity use cases. You will work with CISOs, security executives, application security leaders, SOC teams, security engineering teams, and hands-on practitioners to identify where AI can create measurable security outcomes. This is a customer-facing technical role for someone who can move fluidly between executive strategy, practitioner-level cyber depth, and hands-on solution design. You will help customers evaluate and deploy workflows such as secure code review, vulnerability triage, threat modeling, remediation, SOC and incident response workflows, detection engineering, cloud security, GRC automation, and security validation. You will collaborate closely with Sales, Solutions Engineering, Product, Engineering, Research, and Security to turn customer needs into safe deployment patterns, reusable field assets, and product feedback. This role is based in our San Francisco HQ. We offer relocation support to new employees. In this role, you will: Deeply embed with strategic customers as the technical lead for AI-enabled cybersecurity wo

We are seeking an experienced Senior Generative AI Developer to help drive the design, development, and integration of state-of-the-art Generative AI and agentic AI solutions across our enterprise Controls Technology platform. You will collaborate with cross-functional teams, contribute deep technical expertise in context engineering, retrieval systems, knowledge graphs, and multi-agent orchestration, and play a key role in delivering scalable, grounded AI solutions to enhance automation and operational efficiency. This role centers on architecting robust applications and agent systems on top of pre-trained and hosted foundation models — not on training or fine-tuning models. Key Responsibilities Collaborate with AI architects, leads, and stakeholders to design and implement generative and agentic AI solutions that address business challenges. Architect advanced context engineering strategies — context layering, chaining, compression, pruning/offloading, and memory management — to maximize reliability, provenance, and token efficiency in production. Design and implement advanced generative AI methods, including sophisticated prompt engineering and Retrieval-Augmented Generation (RAG) . Build and optimize RAG systems , including hybrid search, multi-vector retrieval, and re-ranking pipelines. Design and implement knowledge graphs and Graph RAG architectures to enable multi-hop reasoning, explainability, and traceable, grounded responses for high-value business domains. Architect agentic workflows and multi-agent systems using Google Agent Development Kit (ADK) and comparable frameworks (LangGraph, Microsoft Agent Framework, CrewAI), applying orchestration patterns such as supervisor/worker, hierarchical, and peer-to-peer. Design robust agent harnesses — governance, constraints, feedback loops, state/session management, and

About the Team The Code Quality team sits within the Developer Platform organization and owns the systems that keep DoorDash's codebase healthy and secure as it scales: static analysis, quality gates, test frameworks, regression infrastructure, and tooling. Our job is to make sure the signals engineers rely on before shipping — test results, coverage, performance feedback etc — are fast and trustworthy. The decisions we make about tooling and standards directly shape how confidently and quickly engineering teams at DoorDash can ship to production. About the Role We're looking for Software Engineers to help build and maintain the systems that validate code quality across DoorDash's engineering org, treating our tooling as a critical product for the engineers who rely on it every day: static analysis and quality gates, test frameworks and regression infrastructure. You’ll design the tooling and automation that will help derive trustworthy quality signals, integrate them into the development lifecycle, and make it easy for engineers to execute reliable, repeatable workflows. You will collaborate across the engineering org, partnering directly with the teams who use what you build to understand the accuracy, reliability and performance of their functionality. You will report into the Engineering Manager on our Code Quality team in our Developer Platform organization. You must be located in either San Francisco, CA, Sunnyvale, CA, Los Angeles, CA, Seattle, WA, or New York, NY. You're excited about this opportunity because you will… Build and maintain quality tooling — static analysis, quality gates, coverage reporting, test frameworks, regression infrastructure — and integrate it directly into our developer workflows and CI/CD pipelines Define and derive quality signals - flakiness, pass rate, coverage, performance, scale readiness etc - Build tooling that improves everyday engineering workflows, including local development, CI/CD, debugging, and rollou

About the Role Together AI runs one of the largest GPU fleets in the world. The Infra Agent Systems team builds the software systems that power and automate that infrastructure. We develop production AI agents that diagnose hardware failures, investigate incidents, correlate signals across the fleet, and automate operational workflows. Alongside these agents, we build the platform they run on, including knowledge graphs, retrieval systems, orchestration frameworks, and developer tooling. You’ll work across two areas: Infrastructure Agent Systems — Build production AI agents that help operate our GPU fleet by diagnosing failures, investigating incidents, gathering evidence from live systems, and assisting with remediation. These agents are used every day by our infrastructure and datacenter teams through APIs, CLI, dashboards, and Slack. Core Agent Platform — Build the platform that powers these agents, including knowledge graphs, search and retrieval, orchestration, evaluation, and the tooling that enables agents to reason, act, and continuously improve. We’re working on something that hasn’t really been done before: building knowledge graphs and self-improving AI agents that understand, operate, and continuously improve large-scale AI infrastructure. This is an opportunity to work at the intersection of AI agents, distributed systems, infrastructure, and automation , solving challenging engineering problems with real production impact. There’s an enormous amount to build, learn, and shape as we define the future of autonomous infrastructure. Why this Role You’ll work on two hard problems at the same time: making AI agents trustworthy enough to operate production infrastructure, and building the knowledge, retrieval, and distributed systems that make those agents effective. You’ll have the opportunity to build foundational systems from the ground up, work on infrastructure at massive scale, and help define how self-improving AI agents operate real-world AI infrastru

Every day, tens of millions of people come to Roblox to explore, create, play, learn, and connect with friends in 3D immersive digital experiences– all created by our global community of developers and creators. At Roblox, we’re building the tools and platform that empower our community to bring any experience that they can imagine to life. Our vision is to reimagine the way people come together, from anywhere in the world, and on any device. We’re on a mission to connect a billion people with optimism and civility, and looking for amazing talent to help us get there. A career at Roblox means you’ll be working to shape the future of human interaction, solving unique technical challenges at scale, and helping to create safer, more civil shared experiences for everyone. The Infrastructure Compute Site Reliability Engineering mission is to own and manage the successful operation of our underlying cell infrastructure system, along with elements of service discovery, secrets management and related software layers. We’re looking for a skilled Senior Site Reliability Engineer with strong programming skills to help us build Roblox's private cloud, productionize our growing Kubernetes-based infrastructure, and institute reliability best practices across the Roblox Compute team. You will: Design and Develop systems & libraries that promote fault-tolerance and resilience, automate much of the management and lifecycle of our clusters, and ensure systems are observable. Promote and Institute reliability best practices across the Infra Compute group, drive common reliability initiatives. Provides collaborative technical reviews and operational guidance to strengthen system reliability. Build, Automate and Standardize process automation to create a "golden path" of tooling and platform support that powers the fundamental Roblox ecosystem. Create Tooling that provides production guardrails, by evaluating release candidate capacity with load testing tooling before de

About the Role Together AI runs one of the largest GPU fleets in the world. The Infra Agent Systems team builds the software systems that power and automate that infrastructure. We develop production AI agents that diagnose hardware failures, investigate incidents, correlate signals across the fleet, and automate operational workflows. Alongside these agents, we build the platform they run on, including knowledge graphs, retrieval systems, orchestration frameworks, and developer tooling. You’ll work across two areas: Infrastructure Agent Systems — Build production AI agents that help operate our GPU fleet by diagnosing failures, investigating incidents, gathering evidence from live systems, and assisting with remediation. These agents are used every day by our infrastructure and datacenter teams through APIs, CLI, dashboards, and Slack. Core Agent Platform — Build the platform that powers these agents, including knowledge graphs, search and retrieval, orchestration, evaluation, and the tooling that enables agents to reason, act, and continuously improve. We’re working on something that hasn’t really been done before: building knowledge graphs and self-improving AI agents that understand, operate, and continuously improve large-scale AI infrastructure. This is an opportunity to work at the intersection of AI agents, distributed systems, infrastructure, and automation , solving challenging engineering problems with real production impact. There’s an enormous amount to build, learn, and shape as we define the future of autonomous infrastructure. responsible for delivering the software but also for operating and supporting it in production. Why this Role You’ll work on two hard problems at the same time: making AI agents trustworthy enough to operate production infrastructure, and building the knowledge, retrieval, and distributed systems that make those agents effective. You’ll have the opportunity to build foundational systems from the ground up, work on infrastructur

About the Role Together AI runs one of the largest GPU fleets in the world. The Infra Agent Systems team builds the software systems that power and automate that infrastructure. We develop production AI agents that diagnose hardware failures, investigate incidents, correlate signals across the fleet, and automate operational workflows. Alongside these agents, we build the platform they run on, including knowledge graphs, retrieval systems, orchestration frameworks, and developer tooling. You’ll work across two areas: Infrastructure Agent Systems — Build production AI agents that help operate our GPU fleet by diagnosing failures, investigating incidents, gathering evidence from live systems, and assisting with remediation. These agents are used every day by our infrastructure and datacenter teams through APIs, CLI, dashboards, and Slack. Core Agent Platform — Build the platform that powers these agents, including knowledge graphs, search and retrieval, orchestration, evaluation, and the tooling that enables agents to reason, act, and continuously improve. We’re working on something that hasn’t really been done before: building knowledge graphs and self-improving AI agents that understand, operate, and continuously improve large-scale AI infrastructure. This is an opportunity to work at the intersection of AI agents, distributed systems, infrastructure, and automation , solving challenging engineering problems with real production impact. There’s an enormous amount to build, learn, and shape as we define the future of autonomous infrastructure. responsible for delivering the software but also for operating and supporting it in production. Why this Role You’ll work on two hard problems at the same time: making AI agents trustworthy enough to operate production infrastructure, and building the knowledge, retrieval, and distributed systems that make those agents effective. You’ll have the opportunity to build foundational systems from the ground up, work on infrastructur

About the Role Together AI runs one of the largest GPU fleets in the world. The Infra Agent Systems team builds the software systems that power and automate that infrastructure. We develop production AI agents that diagnose hardware failures, investigate incidents, correlate signals across the fleet, and automate operational workflows. Alongside these agents, we build the platform they run on, including knowledge graphs, retrieval systems, orchestration frameworks, and developer tooling. You’ll work across two areas: Infrastructure Agent Systems — Build production AI agents that help operate our GPU fleet by diagnosing failures, investigating incidents, gathering evidence from live systems, and assisting with remediation. These agents are used every day by our infrastructure and datacenter teams through APIs, CLI, dashboards, and Slack. Core Agent Platform — Build the platform that powers these agents, including knowledge graphs, search and retrieval, orchestration, evaluation, and the tooling that enables agents to reason, act, and continuously improve. We’re working on something that hasn’t really been done before: building knowledge graphs and self-improving AI agents that understand, operate, and continuously improve large-scale AI infrastructure. This is an opportunity to work at the intersection of AI agents, distributed systems, infrastructure, and automation , solving challenging engineering problems with real production impact. There’s an enormous amount to build, learn, and shape as we define the future of autonomous infrastructure. responsible for delivering the software but also for operating and supporting it in production. Why this Role You’ll work on two hard problems at the same time: making AI agents trustworthy enough to operate production infrastructure, and building the knowledge, retrieval, and distributed systems that make those agents effective. You’ll have the opportunity to build foundational systems from the ground up, work on infrastructur

Every day, tens of millions of people come to Roblox to explore, create, play, learn, and connect with friends in 3D immersive digital experiences– all created by our global community of developers and creators. At Roblox, we’re building the tools and platform that empower our community to bring any experience that they can imagine to life. Our vision is to reimagine the way people come together, from anywhere in the world, and on any device. We’re on a mission to connect a billion people with optimism and civility, and looking for amazing talent to help us get there. A career at Roblox means you’ll be working to shape the future of human interaction, solving unique technical challenges at scale, and helping to create safer, more civil shared experiences for everyone. The Infrastructure Compute Site Reliability Engineering mission is to own and manage the successful operation of our underlying cell infrastructure system, along with elements of service discovery, secrets management and related software layers. We’re looking for a skilled Senior Site Reliability Engineer with strong programming skills to help us build Roblox's private cloud, productionize our growing Kubernetes-based infrastructure, and institute reliability best practices across the Roblox Compute team. You will: Design and Develop systems & libraries that promote fault-tolerance and resilience, automate much of the management and lifecycle of our clusters, and ensure systems are observable. Promote and Institute reliability best practices across the Infra Compute group, drive common reliability initiatives. Provides collaborative technical reviews and operational guidance to strengthen system reliability. Build, Automate and Standardize process automation to create a "golden path" of tooling and platform support that powers the fundamental Roblox ecosystem. Create Tooling that provides production guardrails, by evaluating release candidate capacity with load testing tooling before de

About the Team We’re hiring a Developer Productivity engineer to support OpenAI’s Inference Runtime teams. These teams own the systems responsible for serving models reliably, efficiently, and safely across Codex, ChatGPT, API, and internal research workloads. We’re hiring a Developer Productivity Engineer to help scale the engineering systems, safeguards, and developer workflows that enable our teams to move quickly without compromising reliability or performance. This role sits at the intersection of developer experience, CI/CD infrastructure, release engineering, production readiness, and inference systems reliability. You’ll work on the tooling and operational foundations that support model launches, inference optimizations, cloud provider integrations, and large-scale deployments across a rapidly evolving inference stack. About the Role We’re looking for an autonomous, high-ownership engineer who cares deeply about making other engineers faster, safer, and more confident. A major focus of this role will be improving the tooling and infrastructure around deploy gates for inference engine images. These systems help ensure that every image released to production and research is correct, numerically sound, free of regressions, and performant across key metrics like time-to-first-token (TTFT) and time-between-tokens (TBT). You’ll help harden the systems that catch issues before they reach production, reduce noise from flaky or infrastructure-related test failures, and improve automation around triage, ownership, debugging, and escalation when failures occur. You’ll also work on improving observability, rollout safety, release automation, and developer self-service tooling across a rapidly evolving inference stack. This is not generic internal tools work. The systems you build directly impact OpenAI’s ability to support new model launches, safely ship inference optimizations to the world, onboard new infrastructure providers, and operate one of the largest and most p

About the Team The ChatGPT Velocity team owns the health of the end-to-end developer and deploy loop for ChatGPT-facing services. Our mission is to help ChatGPT engineers ship confidently with a fast, lightweight development cycle and a trusted path to production. ChatGPT development depends on a long chain: local environments, Bazel builds, CI, tests, merges, release candidates, deploys, synthetics, alerts, and production health. When any link is slow, flaky, or unclear, engineers lose hours, fixes reach users later, and on-call load rises. This team turns that cross-cutting drag into owned, measured, and durable improvements. About the Role We are hiring an experienced infrastructure engineer to make ChatGPT development dramatically faster and more reliable. You will work across local development, build systems, CI, deployment infrastructure, test ownership, and production safety signals to reduce the time and attention required to move a healthy change from development to production. This is not a narrow tooling role. The best person for this job will be comfortable diagnosing messy distributed systems, reading developer pain signals from Slack and metrics, building reliable automation, negotiating ownership across teams, and making tradeoffs between velocity and production safety. You should enjoy treating engineers as users and turning confusing workflow failures into clear, measured systems. In this role, you will: Reduce local development startup and iteration latency for ChatGPT engineers Improve Bazel and build performance for local machines, devboxes, and CI, including cache effectiveness, reproducibility, disk usage, remote cache behavior, and observability into invalidations. Improve CI reliability and merge throughput by reducing unrelated failures, tail latency, flaky or mis-owned tests, quarantine friction, and repeated manual reruns. Build agents that help PRs make forward progress: rebasing, conflict resolution, CI triage, safe reruns, owner routing

About Pinecone Pinecone is the leading vector database for building accurate and performant AI applications at scale in production. Pinecone's mission is to make AI knowledgeable. More than 5000 customers across various industries have shipped AI applications faster and more confidently with Pinecone's developer-friendly technology. Pinecone is based in New York and raised $138M in funding from Andreessen Horowitz, ICONIQ, Menlo Ventures, and Wing Venture Capital. About the Team and Role: As a Business Development Representative, you’ll be the primary catalyst for user activation and expansion. You will work at the critical intersection of our Product-Led Growth (PLG) motion and our high-growth revenue engine. Your core mission is to identify high-potential users within our self-serve funnel and proactively convert them into qualified sales opportunities. You are part researcher and part automation hacker. You will partner closely with our Revenue Operations team to combine creative outreach with GTM (Go-To-Market) engineering workflows (using tools like Clay, n8n, Zapier, etc.) to deliver personalized, data-backed touchpoints at scale. You'll collaborate closely with Sales, Customer Success, and Solutions Engineering to accelerate our PLG motion, turning a robust sign ups & usage funnel into a predictable revenue engine and setting a new standard for AI-native GTM. Responsibilities: Drive Sales Opportunities: Proactively engage users exhibiting high-potential usage signals (e.g., specific API patterns, advanced feature experimentation, new workspace invites) to guide them toward opportunities for the sales team. Identify & Convert: Execute highly personalized, data-driven outreach sequences to connect with AI practitioners, technical leads, and business decision-makers. Your goal is to understand their platform behaviors and signals in order to generate qualified sales leads. Surface PQLs: Partner with RevOps and Growth to analyze product telemetry and surf

About Vercel: Vercel is the agentic infrastructure company, freeing people and agents to ship what's next. For more than a decade we've helped builders move from idea to production with speed, security, and exceptional developer experience. Now we're scaling our products for both agents and people to ship and run software, built in the open and trusted by OpenAI, PayPal, Ramp, Supreme, and millions of developers worldwide. About the role: We are looking for a Head of Field Engineering Operations to join our Revenue Operations team. You'll be a strategic partner to the VP of Field Engineering and build the systems, processes, and team that help our Field Engineering organization scale You will build and lead a team while constantly asking how we can use better tooling, smarter automation, and tighter feedback loops to make the organization faster and sharper. You will report to the VP of Revenue Operations. If you’re based within a pre-determined commuting distance of one of our offices (SF, NYC, or Austin), the role includes in-office anchor days on Monday, Tuesday, and Friday. For location-specific details, please connect with our recruiting team. What you will do: Design the processes, systems, and operating cadences that let Solutions Architects, Developer Success Engineers, Customer Success Engineers, Technical Account Managers, and Professional Services scale Build and lead the Field Engineering Operations team, and set team structures, role definitions, and engagement models as Field Engineering grows Run capacity planning, territory design, and resource allocation across the Americas, Europe, the Middle East and Africa (EMEA), and Asia-Pacific (APAC), in step with go-to-market (GTM) teams Own the pre-sales to post-sales lifecycle framework, including technical win and onboarding forecasts, go-live tracking, and consumption ramp measurement Define the Field Engineering metrics, dashboards, and health scoring models that show team performance, accoun

About Vercel: Vercel is the agentic infrastructure company, freeing people and agents to ship what's next. For more than a decade we've helped builders move from idea to production with speed, security, and exceptional developer experience. Now we're scaling our products for both agents and people to ship and run software, built in the open and trusted by OpenAI, PayPal, Ramp, Supreme, and millions of developers worldwide. About the Role: Vercel is looking for engineers to help us build functional systems that improve product and customer experience. As a member of the Edge team, you will help to scale and improve our infrastructure, availability and reliability by working with our backend engineers and product team to identify problems, create tooling and automation. Your role will be dynamic - you should be comfortable designing systems, writing code, and debugging systems in production. Our team orchestrates deploying, routing and serving for our customers through capabilities and tooling we maintain that leverage our own and other cloud providers' infrastructure for networking, TLS termination, routing, storage, caching and other novel edge services. If you’re based within a pre-determined commuting distance of one of our offices (SF or NY), the role includes in-office anchor days on Monday, Tuesday, and Friday. If you're located beyond that distance, the role is fully remote. For location-specific details, please connect with our recruiting team. About You: Intrigued about tackling the complex challenges serving petabytes of data and billions of requests to millions of people A collaborative team player who believes in the power of strong teams to drive significant changes and innovations Have at least 5 years of relevant experience Have deep experience with how to make high performance systems scale in the cloud Want to help protect the Vercel platform and our customers from abuse Are keen to experiment, challenge norms and deliver secure and reliable systems