Ai Systems Engineer in United States

AI Systems Engineer - Codex Core Agents About The Team The Codex Core Agents team builds the agent harness that turns model capability into real-world action. We own the systems around the model: prompting and interpreting model outputs, executing actions safely in real environments, and feeding production experience back into better models and better agent behavior. This team sits close to research and works across the stack: harness, model interaction, inference, sandboxed execution, orchestration, evals, production reliability, and the performance envelope around tokens, latency, cost, capacity, and quality. The harness is open source and increasingly part of how models are trained and evaluated, making this one of the highest-leverage layers in Codex. About The Role We’re looking for engineers to build the AI systems that make Codex agents dependable in production. The ideal candidate is an agent-systems builder: hands-on across low-level systems and ML workflows, able to debug Codex behavior end to end across the harness, model behavior, inference/runtime stack, GPU fleet, and product surface. You’ll work with research, infrastructure, and product to design agent harness capabilities, run experiments and ablations across the model + system prompt + harness stack, build frameworks for assessing production agent performance, and turn messy failures into durable improvements. What You’ll Do Design and build the core agent harness and execution loop that lets Codex agents interpret model outputs, use tools, execute code, and complete long-horizon tasks safely. Build sandboxing, isolation, orchestration, state, and workflow infrastructure for agents operating in real development environments. Develop evaluation, experimentation, and debugging systems that distinguish harness issues, model behavior, inference/runtime issues, and product failures. Run ablations across prompts, model-facing interfaces, context construction, tool-use strategies, and harness behavior to

About the Team The Recursive Self-Improvement (RSI) team works across research, engineering, product, and infrastructure to build AI systems that accelerate and ultimately conduct high-quality research at OpenAI. We work to automate real research workflows and improve research productivity by building systems and feedback loops, designing evaluations, and training models to develop missing capabilities. Our work spans the full lifecycle of model training, evaluation, and deployment to help researchers move faster and tackle increasingly ambitious problems. About the Role We’re hiring research scientists , research engineers , and AI systems engineers to work on automating research at OpenAI. This role is based in San Francisco, CA. In this role, you will: Design evaluations for research judgment, hypothesis generation and testing, and long-horizon experiment execution. Turn real research workflows and model failures into data and evaluation flywheels. Improve model research capabilities through agent harnesses, synthetic data, RL environments, and model training. Build and maintain safe, reliable integrations between our models and OpenAI’s research infrastructure. Develop research agents, experiment-orchestration systems, and sandboxed runtimes that support real research workflows. Create metrics and economic models to understand RSI’s current and future effects on research productivity, model capabilities, and the safety of internal deployments. This is a high-ownership role for researchers and engineers who thrive in ambiguity, move fluidly between research and implementation, and turn emerging opportunities into rigorous, reliable, scalable results. You might thrive in this role if you: Have research or engineering experience across LLM training, model evaluations, agent systems, synthetic data, research infrastructure, or large-scale distributed systems. Are a strong generalist who can move between open-ended research and practical implementation, turning ambig

Tenstorrent is leading the industry on cutting-edge AI technology, revolutionizing performance expectations, ease of use, and cost efficiency. With AI redefining the computing paradigm, solutions must evolve to unify innovations in software models, compilers, platforms, networking, and semiconductors. Our diverse team of technologists have developed a high performance RISC-V CPU from scratch, and share a passion for AI and a deep desire to build the best AI platform possible. We value collaboration, curiosity, and a commitment to solving hard problems. We are growing our team and looking for contributors of all seniorities. Tenstorrent is seeking a senior High Speed Interconnect / Signal Integrity Engineer to design and validate high-bandwidth links for large-scale AI systems. You will define, model, and qualify interconnect solutions across copper and optical technologies for next-generation AI inference and training clusters. This role is on-site in Santa Clara, CA, Austin, TX, or Toronto, Canada. We welcome candidates at various experience levels. During the interview process, candidates will be assessed for the appropriate level, and offers will align with that level, which may differ from the one in this posting Who You Are An experienced electrical engineer with a Bachelor’s or Master’s in Electrical Engineering. 5+ years working on high-speed communications (100G–1.6T), including signal integrity, channels, and links. Comfortable building and owning link and channel budgets and making clear tradeoffs between reach, loss, BER, and margin. Hands-on with SI tools and lab equipment such as Keysight ADS, VNAs, TDRs, BERTs, and protocol analyzers. Familiar with cable specification and testing, as well as accelerated life testing, mating life, and failure analysis. Able to collaborate across hardware, systems, and manufacturing teams; manufacturing/DFM/DTM experience is a plus. What We Need Define and specify high-speed interconnect architectures

At ClickUp, we're building the future of work: the first truly converged AI workspace unifying tasks, docs, chat, calendar, and enterprise search, all supercharged by context-driven AI. We are an AI-native company. Every team member is expected to leverage AI daily, and we evaluate AI fluency as part of our hiring process. Join us and help redefine what's possible. 🚀 Job Summary As a Business Systems Engineer on the GTM Engineering team, you will design, build, and operate the automation and AI systems that power ClickUp's Go-To-Market business — spanning core business products and the integration platforms that connect them. This role is AI-native at its core: you won't just maintain existing workflows, you'll actively advance our GTM systems with intelligent agents, LLM-powered automations, and next-generation integration patterns built on MCP, ClickUp Super Agents, and modern iPaaS tooling. You'll sit at the intersection of business systems architecture and applied AI — partnering with Sales, Finance, Revenue Operations, and fellow GTM Systems engineers to eliminate toil, accelerate revenue workflows, and build the automated, AI-augmented infrastructure the company runs on. This is a hands-on engineering role for someone deeply fluent in enterprise business systems, excited about deploying production AI, and committed to genuine ownership of the platforms they build — directly supporting GTMSOE's broader mission of operational excellence across the GTM org. Key Responsibilities AI-Native Automation & Agent Development Design and build AI-powered automations and agentic workflows across the GTM tech stack — including Salesforce, NetSuite, Workato, and MuleSoft — to eliminate manual effort and accelerate business operations. Develop and deploy ClickUp Super Agents and LLM-based automations to automate tasks such as deal data enrichment, quote generation assistance, order validation, revenue recognition triggers, and exception handling in quote-to-cash workflow

About us Graphcore is one of the world’s leading innovators in Artificial Intelligence compute. It is developing hardware, software and systems infrastructure that will unlock the next generation of AI breakthroughs and power the widespread adoption of AI solutions across every industry. As part of the SoftBank Group, Graphcore is a member of an elite family of companies responsible for some of the world’s most transformative technologies. Together, they share a bold vision: to enable Artificial Super Intelligence and ensure its benefits are accessible to everyone. Graphcore’s teams are drawn from diverse backgrounds and bring a broad range of skills and perspectives. A melting pot of AI research specialists, silicon designers, software engineers and systems architects, Graphcore enjoys a culture of continuous learning and constant innovation. Job Summary We are seeking a Staff Hardware Engineer to provide advanced operational, diagnostic, and engineering support for Graphcore’s Arm-based hardware platforms across lab and data center environments. This role focuses on supporting hardware bring-up, validation, and troubleshooting of complex AI compute platforms, including server blades, racks, and rack-scale infrastructure. The successful candidate will collaborate closely with engineering, platform, and data center teams to ensure the reliability and performance of next-generation AI systems. The Team The Systems Engineering and Hardware Engineering teams are responsible for enabling the bring-up, validation, and operational reliability of Graphcore’s AI infrastructure platforms. The team works closely with server engineering, firmware teams, platform architects, and data center operations to support the development, testing, and deployment of next-generation AI compute systems. This collaborative environment enables rapid problem-solving and continuous improvement of Graphcore’s hardware platforms from early development through production deployment.

About the Team The Codex team is responsible for building state-of-the-art AI systems that can write code, reason about software, and act as intelligent agents for developers and non-developers alike. Our mission is to push the frontier of code generation and agentic reasoning, and deploy these capabilities in real-world products such as ChatGPT and the API, as well as in next-generation tools specifically designed for agentic coding. We operate across research, engineering, product, and infrastructure—owning the full lifecycle of experimentation, deployment, and iteration on novel coding capabilities. About the Role As a Performance & Systems Engineer on the Codex team, you will be responsible for whole-system optimization across a complex, evolving stack. Codex spans LLM inference, cloud orchestration, agentic work management, and multiple product surfaces. Your job will be to identify and land high-leverage changes—across infrastructure, modeling, and product layers—that make Codex agents significantly faster and cheaper to serve. We’re looking for generalists who thrive in ambiguity and love chasing performance bottlenecks to ground. This is a high-ownership role where your work will directly improve the experience of millions of users. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. In this role, you will: Hunt down and address inefficiencies across the Codex system stack, from agent behavior to LLM inference to container orchestration, and beyond. Build tooling to measure, profile, and optimize system performance at scale. Collaborate with researchers and engineers to land high-ROI changes that improve latency and cost. You might thrive in this role if you: Have experience operating across both ML systems and cloud infrastructure. Enjoy diving into messy, ambiguous problems and emerging with clear wins. Think holistically about performance, balancing spee

About Graphcore Graphcore is a global leader in artificial intelligence computing systems. We design advanced semiconductors and data center hardware that provide the specialized processing power needed to advance AI while improving the efficiency required for broad adoption. As part of SoftBank Group, Graphcore belongs to a family of companies developing transformative technologies. Our AI Engineering Campus in Austin plays an important role in building the hardware platforms that support the next generation of AI systems. The Opportunity We are looking for a recent graduate or early-career engineer to join the Hardware Platform Development team as a Graduate Systems Engineer. You will contribute to the design, integration, validation, and performance analysis of advanced AI compute platforms. You will work with experienced hardware, firmware, software, mechanical, thermal, and systems engineers throughout the development lifecycle. The role combines subsystem engineering, hands-on laboratory work, test automation, data analysis, troubleshooting, and clear technical documentation. Start: September, 2027 Location: Austin, Texas, USA What You Will Do Contribute to the design, integration, and testing of CPU and high-speed input and output subsystems for advanced compute platforms. Take ownership of defined engineering tasks from requirements and test planning through execution, analysis, and technical review. Develop system-level validation plans, procedures, scripts, and tools that improve test coverage, repeatability, data collection, and analysis. Evaluate platform performance, power, signal behavior, reliability, and interoperability using laboratory measurements and system data. Investigate emerging input and output technologies, including PCIe 6.0 and 800G Ethernet, and assess their use in advanced computing systems. Support platform power, cooling, and energy-efficiency investigations, including liquid-cooling systems for high-performance processor

About us Graphcore is one of the world’s leading innovators in Artificial Intelligence compute. It is developing hardware, software and systems infrastructure that will unlock the next generation of AI breakthroughs and power the widespread adoption of AI solutions across every industry. As part of the SoftBank Group, Graphcore is a member of an elite family of companies responsible for some of the world’s most transformative technologies. Together, they share a bold vision: to enable Artificial Super Intelligence and ensure its benefits are accessible to everyone. Graphcore’s teams are drawn from diverse backgrounds and bring a broad range of skills and perspectives. A melting pot of AI research specialists, silicon designers, software engineers and systems architects, Graphcore enjoys a culture of continuous learning and constant innovation. Job Summary We are seeking a Staff Hardware Engineer to provide advanced operational, diagnostic, and engineering support for Graphcore’s Arm-based hardware platforms across lab and data center environments. This role focuses on supporting hardware bring-up, validation, and troubleshooting of complex AI compute platforms, including server blades, racks, and rack-scale infrastructure. The successful candidate will collaborate closely with engineering, platform, and data center teams to ensure the reliability and performance of next-generation AI systems. The Team The Systems Engineering and Hardware Engineering teams are responsible for enabling the bring-up, validation, and operational reliability of Graphcore’s AI infrastructure platforms. The team works closely with server engineering, firmware teams, platform architects, and data center operations to support the development, testing, and deployment of next-generation AI compute systems. This collaborative environment enables rapid problem-solving and continuous improvement of Graphcore’s hardware platforms from early development through production deployment.

About us Graphcore is one of the world’s leading innovators in Artificial Intelligence compute. It is developing hardware, software and systems infrastructure that will unlock the next generation of AI breakthroughs and power the widespread adoption of AI solutions across every industry. As part of the SoftBank Group, Graphcore is a member of an elite family of companies responsible for some of the world’s most transformative technologies. Together, they share a bold vision: to enable Artificial Super Intelligence and ensure its benefits are accessible to everyone. Graphcore’s teams are drawn from diverse backgrounds and bring a broad range of skills and perspectives. A melting pot of AI research specialists, silicon designers, software engineers and systems architects, Graphcore enjoys a culture of continuous learning and constant innovation. Job Summary We are seeking a Staff Hardware Engineer to provide advanced operational, diagnostic, and engineering support for Graphcore’s Arm-based hardware platforms across lab and data center environments. This role focuses on supporting hardware bring-up, validation, and troubleshooting of complex AI compute platforms, including server blades, racks, and rack-scale infrastructure. The successful candidate will collaborate closely with engineering, platform, and data center teams to ensure the reliability and performance of next-generation AI systems. The Team The Systems Engineering and Hardware Engineering teams are responsible for enabling the bring-up, validation, and operational reliability of Graphcore’s AI infrastructure platforms. The team works closely with server engineering, firmware teams, platform architects, and data center operations to support the development, testing, and deployment of next-generation AI compute systems. This collaborative environment enables rapid problem-solving and continuous improvement of Graphcore’s hardware platforms from early development through production deployment.

Our vision is to transform how the world uses information to enrich life for all . Micron Technology is a world leader in innovating memory and storage solutions that accelerate the transformation of information into intelligence, inspiring the world to learn, communicate and advance faster than ever. Job Summary We are seeking a motivated engineer to join the DRAM Systems Engineering team, focusing on the development, evaluation, and optimization of next-generation memory systems for AI accelerators. This role emphasizes research and development across hardware architecture, operating systems, and performance analysis to support Agentic AI inference workloads. If you are ambitious and eager to make an impact in the exciting world of AI and memory systems, this is the perfect opportunity for you! Responsibilities Characterize AI inference workloads and examine memory behavior Build and evaluate tiered memory hierarchies for AI accelerators Study KV cache lifecycles, MoE models, and data placement strategies Compare and optimize explicit versus hardware-assisted data movement Develop, test, debug, and detail system-level and OS components Prototype and evaluate agentic AI systems by building agents and multi-agent workflows using modern frameworks and orchestration patterns (planning, tool use, memory, and context management). Apply these technologies both as workloads under study and as accelerators for internal engineering workflows <h2 style="color:!importan

About the Team pAGI Infra team builds and operates the systems that make large-scale model training and evaluation reliable, efficient, and easy to run. Our work spans distributed training infrastructure, inference and grading platforms, compute scheduling, and research tooling. We partner closely with researchers and engineering teams to turn new research needs into dependable infrastructure, improve GPU efficiency, and shorten the path from an experiment to a validated model. About the Role We’re looking for an AI Systems Engineer to help scale the infrastructure behind our training and evaluation workflows. You’ll own projects from identifying bottlenecks and designing solutions through deployment and operation. The work combines distributed systems engineering, performance optimization, and close collaboration with researchers. You might build a shared grading service, improve resource allocation across workloads, or bring a new training stack into production — directly improving how quickly and reliably research moves forward. In this role, you will: Build and operate infrastructure for large-scale training and evaluation, improving reliability, throughput, and resource efficiency. Develop shared inference and grading platforms with automated capacity management, health monitoring, and visibility into performance. Improve compute scheduling and resource allocation to reduce idle GPU time and help workloads recover quickly from failures. Diagnose bottlenecks across training, inference, and orchestration, and work across teams to improve end-to-end performance. Build self-service tools, automated validation, and observability that help researchers launch experiments, diagnose issues, and compare results with less manual intervention. You might thrive in this role if you: Are excited about the potential of personal AGI and want to build the infrastructure that enables it. Have strong software engineering fundamentals and experience building or operating large-scal

Our vision is to transform how the world uses information to enrich life for all . Micron Technology is a world leader in innovating memory and storage solutions that accelerate the transformation of information into intelligence, inspiring the world to learn, communicate and advance faster than ever. Micron Technology is a world leader in innovating memory and storage solutions that accelerate the transformation of information into intelligence, inspiring the world to learn, communicate and advance faster than ever. As an AI Reimagination Engineer in Micron's Generative AI Center of Excellence (GenAI COE), you have an outstanding chance to transform how businesses function. You will partner with different business areas to break down large, manual, multi-step processes and redesign them into effective, autonomous systems. This position combines process reimagination with AI systems engineering, making you a key part of the transformation journey. You will collaborate closely with the GenAI COE, IT architecture, security, and project teams. You will lead projects from the initial redesign to the final build, delivering solutions that business teams can adopt and scale. Responsibilities: Decompose end-to-end processes: Map current-state flows, quantify effort and risk, and lead eliminate/simplify/agentify analysis before automation. Architect the agentic solution: Build future-state flows and AI architecture, including task and agent decomposition, orchestration patterns, tool and data access, memory and context strategy, and human-in-the-loop controls. Translate inventions into buildable solutions by developing agent workflows, composing prompt and context strategies, MCP/connector and integration requirements, and evaluation criteria. Follow Micron's “Secure by Design”

Our vision is to transform how the world uses information to enrich life for all . Micron Technology is a world leader in innovating memory and storage solutions that accelerate the transformation of information into intelligence, inspiring the world to learn, communicate and advance faster than ever. Micron Technology is a world leader in innovating memory and storage solutions that accelerate the transformation of information into intelligence, inspiring the world to learn, communicate and advance faster than ever. As an AI Reimagination Engineer in Micron's Generative AI Center of Excellence (GenAI COE), you have an outstanding chance to transform how businesses function. You will partner with different business areas to break down large, manual, multi-step processes and redesign them into effective, autonomous systems. This position combines process reimagination with AI systems engineering, making you a key part of the transformation journey. You will collaborate closely with the GenAI COE, IT architecture, security, and project teams. You will lead projects from the initial redesign to the final build, delivering solutions that business teams can adopt and scale. Responsibilities: Decompose end-to-end processes: Map current-state flows, quantify effort and risk, and lead eliminate/simplify/agentify analysis before automation. Architect the agentic solution: Build future-state flows and AI architecture, including task and agent decomposition, orchestration patterns, tool and data access, memory and context strategy, and human-in-the-loop controls. Translate inventions into buildable solutions by developing agent workflows, composing prompt and context strategies, MCP/connector and integration requirements, and evaluation criteria. Follow Micron's “Secure by Design”

Our vision is to transform how the world uses information to enrich life for all . Micron Technology is a world leader in innovating memory and storage solutions that accelerate the transformation of information into intelligence, inspiring the world to learn, communicate and advance faster than ever. Micron Technology is a world leader in innovating memory and storage solutions that accelerate the transformation of information into intelligence, inspiring the world to learn, communicate and advance faster than ever. As an AI Reimagination Engineer in Micron's Generative AI Center of Excellence (GenAI COE), you have an outstanding chance to transform how businesses function. You will partner with different business areas to break down large, manual, multi-step processes and redesign them into effective, autonomous systems. This position combines process reimagination with AI systems engineering, making you a key part of the transformation journey. You will collaborate closely with the GenAI COE, IT architecture, security, and project teams. You will lead projects from the initial redesign to the final build, delivering solutions that business teams can adopt and scale. Responsibilities: Decompose end-to-end processes: Map current-state flows, quantify effort and risk, and lead eliminate/simplify/agentify analysis before automation. Architect the agentic solution: Build future-state flows and AI architecture, including task and agent decomposition, orchestration patterns, tool and data access, memory and context strategy, and human-in-the-loop controls. Translate inventions into buildable solutions by developing agent workflows, composing prompt and context strategies, MCP/connector and integration requirements, and evaluation criteria. Follow Micron's “Secure by Design”

About the Team We’re hiring Software Engineers to join our broader Infrastructure organization, which supports multiple high-impact teams. Depending on your interests and experience, you could work on one of several focus areas—including Core Distributed Systems, Reliability Engineering, Observability, Developer Productivity or Cloud Infrastructure. About the Role All teams are deeply collaborative, work on mission-critical services, and are responsible for building distributed, scalable infrastructure to bring OpenAI’s technology to the world through products like ChatGPT and the OpenAI API. You’ll work closely with stakeholders to understand infrastructure, data and compute needs, setting the technical strategy that supports cutting-edge research and product development. This is a critical role for someone who is passionate about solving complex engineering problems at scale, ensuring their performance, scalability and reliability Team Focus Areas Distributed Systems: Owning and building important, highly scalable, available, performant, and reliable distributed systems (and their building blocks) to power the entire stack at OpenAI Systems Engineering: Work across layers of the stack—debugging system bottlenecks, evolving core infrastructure, and solving novel problems in performance and scalability. Reliability Engineering: Build scalable, fault-tolerant systems and lead efforts around service health, incident response, and resilience. Observability: Design and maintain observability tooling (metrics, logs, tracing) to give teams visibility into production systems at scale. Developer Productivity: Create tools, environments, and workflows that help engineers ship high-quality software faster and more safely. Cloud Infrastructure: Own the cloud-native infrastructure (compute, networking, storage) that underpins all services and research workloads. Databases: Building high performance, distributed database systems that power all of OpenAI's product stack. In this