Design And Cost Estimation Head Jobs

About the Team OpenAI's GTM Partnerships team builds a strategic, global partner ecosystem to accelerate customer success, enable enterprise AI adoption, and drive durable growth in support of OpenAI's mission toward AGI. We work cross-functionally across Product, Engineering, Security, Legal, Marketing, Customer Success, and Sales to turn strategic partnerships into measurable business outcomes. This role sits within the GTM Partnerships organization and is responsible for leading OpenAI's strategic relationships with three of the world's largest Global Systems Integrators (GSIs): HCLTech, Wipro, and Cognizant . These partners play a critical role in helping enterprise customers design, deploy, and scale AI solutions by combining OpenAI's technology with deep industry expertise, consulting capabilities, and global delivery organizations. This role reports to the Head of GSIs and will be responsible for driving executive alignment, joint go-to-market strategy, commercial execution, and scalable partnership programs across these strategic accounts. About the Role We are hiring a Partner Director, HCL, Wipro & Cognizant to lead and grow three of OpenAI's most strategic Global Systems Integrator partnerships. You will own executive relationships, develop and execute joint business plans, and drive coordinated go-to-market motions that accelerate customer adoption and revenue growth. This is a highly strategic, externally facing role that requires a blend of executive relationship management, commercial leadership, operational excellence, and ecosystem expertise. You'll work closely with OpenAI Sales, Solutions Engineering, Customer Success, Product, Marketing, Legal, Security, and partner leadership teams to build repeatable motions that generate pipeline, enable successful customer deployments, and deepen long-term strategic alignment. The ideal candidate understands how large consulting organizations operate, has experience driving revenue through strategic partn

About the Team OpenAI is evaluating multiple infrastructure pathways, including powered land, colo/BTS, and NeoCloud opportunities. The Site Readiness & Development team provides the diligence layer needed to compare opportunities, identify risk, and support credible deployment decisions across those pathways. About the Role The NeoCloud & Colo Due Diligence Lead will evaluate third-party infrastructure opportunities where OpenAI is considering deployment through NeoCloud, colo, or BTS structures. This role will focus on facility and deployment readiness, including MEP readiness, rack strategy, developer capability, facility design, power deliverability, schedule credibility, and operating assumptions. Unlike the land diligence team, this role is centered on technical and operational readiness of third-party infrastructure rather than greenfield site master planning, civil development, and entitlement strategy. This is an individual contributor lead role and does not have direct reports initially. The role determines whether each opportunity is fit-for-use and fit-for-service against OpenAI facility, rack, power, network, reliability, and operational standards; identifies material deficiencies and tracks remediation with developers/operators; and evaluates commissioning, validation, AHJ/code, and deployment interfaces such as structured cabling, network readiness, and high-density rack support where relevant. Key Responsibilities Lead diligence on NeoCloud, colo, and BTS opportunities across technical and operational readiness dimensions. Assess each opportunity against OpenAI facility, rack, power, network, reliability, and operational standards to determine deployment fit. Validate MEP readiness, rack deployment strategy, facility design assumptions, power deliverability, and schedule credibility. Identify material deficiencies and work with developers/operators to define remediation plans, owners, timing, and residual risk. Review reliability, availabilit

About the Team: The Shopping team is building the future of how people discover, evaluate, and purchase products through AI. Our mission is to help users make better purchasing decisions by combining OpenAI’s models with rich product information, merchant ecosystems, and personalized experiences. We sit at the intersection of AI, commerce, search, recommendations, and consumer product experiences, partnering closely with product, engineering, research, design, and business teams to reimagine shopping for the AI era. About the Role: As a Product Manager on the Shopping team, you’ll define and build the next generation of AI-powered shopping experiences within ChatGPT. You’ll be responsible for understanding user needs, identifying opportunities to improve product discovery and decision-making, and delivering experiences that help users confidently find and purchase the products that are right for them. You’ll work across a broad set of domains, including search, recommendations, personalization, merchant and product ecosystems, and conversational commerce. This role requires strong product judgment, comfort operating in ambiguity, and the ability to balance user value, business objectives, and technical constraints. You’ll partner closely with engineers, designers, researchers, and cross-functional stakeholders to bring new shopping experiences from concept to scale. This is an opportunity to help define an entirely new category at the intersection of AI and commerce, shaping how millions of users discover and buy products in the future. This position is based in San Francisco, CA, with relocation assistance available. In this role, you will: Define and drive the product vision for shopping experiences in ChatGPT. Partner with research teams to explore how AI can help users discover, evaluate, and confidently purchase products. Collaborate with cross-functional teams—including design, engineering, product, and go-to-market—to build and scale AI-native shopping experi

About the Team The Private Computing team works across product, engineering, security, and safety to build advanced privacy products and infrastructure at OpenAI. Our mission is to provide world-class security features to users so their private data remains private, even from OpenAI. We use technologies like confidential computing, trusted execution environments, and end-to-end encryption to ship product features across ChatGPT, the API, and our future consumer devices. About the Role We’re looking for software engineers to design, build, and scale novel privacy features and infrastructure across ChatGPT, API, and future consumer devices. In this role, you will: Ship fast while balancing difficult trade-offs in complex domains Build core abstractions for trusted execution environments and end-to-end-encryption Build product features for private inference and storage across ChatGPT, API, and future consumer devices Update build systems to increase trust and verifiability Integrate with safety and integrity infrastructure Operate systems at scale with high reliability, including an on-call rotation Collaborate with a diverse set of cross-functional teams across product, engineering, security, safety, policy, and legal You might thrive in this role if you: Care deeply about user privacy and security Have 5+ years of experience in professional software engineering Have experience building and scaling confidential computing or encryption technologies in production environments Have experience with Kubernetes and cloud orchestration systems Take pride in building and operating scalable, reliable, secure systems Can collaborate well and drive alignment in the face of difficult trade-offs Are comfortable with ambiguity and rapid change Workplace & Location This role is based in San Francisco, CA. We follow a hybrid model with 4 days a week in the office and offer relocation assistance to new employees. About OpenAI OpenAI is an AI research and deployment company dedicat

About the Team The Procurement organization enables OpenAI's mission by ensuring every dollar is spent responsibly, compliantly, and efficiently. Within Procurement, the Center of Excellence (COE) team is responsible for designing and scaling the processes, systems, governance, and operating models that enable Procurement to grow effectively alongside the business. This role partners closely with Procurement and cross-functional teams to simplify how work gets requested, routed, approved, and managed across the spend lifecycle. By combining program leadership, process design, and change enablement, we help Procurement scale while maintaining strong controls and delivering an exceptional experience for employees and business partners. About the Role As Procurement Portfolio & Delivery Lead, you will lead complex, cross-functional initiatives that span Strategic Sourcing, Procure-to-Pay (P2P), Extended Workforce, Travel & Expense, Corporate Card, Risk, Legal, Finance, and Technology teams. You will not only drive project and program execution, but also actively contribute to solution design, requirements development, process optimization, testing, rollout planning, and stakeholder alignment. This is a highly collaborative role for someone who thrives in fast-moving environments, can bring structure to ambiguity, and is equally comfortable facilitating executive discussions, building project plans, and rolling up their sleeves to help move initiatives forward. 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: Lead cross-functional procurement transformation programs spanning Strategic Sourcing, P2P, Extended Workforce, T&E, Corporate Card, Risk, and Procurement Systems. Develop and maintain the Procurement transformation roadmap, partnering across teams to identify opportunities, prioritize initiatives, map dependencies, sequence work

About the Team At OpenAI, our User Safety & Risk Operations (USRO) team helps protect our products and users from abuse, fraud, safety risks, and other forms of misuse. We operate at the front line of real-world safety and risk management, translating user and operational signals into timely decisions, effective interventions, and improvements to our systems. This role sits on a new team within USRO focused on building operational capacity for new, ambiguous, or fast-moving areas of work. The team helps define what needs to be built, creates the operating model to support it, and works with partner teams to make the work scalable and durable over time. As a Strategic Operations Lead, you will focus on large, cross-functional initiatives that require clear thinking, technical fluency, strong execution, and the ability to bring structure to undefined problems. About the Role We are seeking a Strategic Operations Lead to drive new and existing strategic operating builds across User Safety & Risk Operations. This is a senior IC role for someone who can turn broad, undefined priorities into clear operating models, launch plans, requirements, stakeholder alignment, documentation, reporting, and execution rhythms. This role will often support initiatives where OpenAI is developing new products or partnerships and the operating model is still being defined. These programs have a direct user safety and risk nexus because new deployment models can change what signals OpenAI can see, who owns response decisions, and how user-impacting risks are detected, escalated, and resolved. You will clarify what OpenAI owns, what partner teams own, what signals we can reliably monitor, how issues should be escalated, and how the workflow should evolve from launch support into a durable operating model. The right person is highly strategic and deeply practical. They can move from executive-level framing to detailed workflow design, stakeholder management, SOPs, launch readiness, ri

About the team OpenAI’s Forward Deployed Engineering team partners with customers to turn research breakthroughs into production systems. We operate at the intersection of customer delivery and core platform development. About the role Forward Deployed Engineers (FDEs) lead complex end-to-end deployments of frontier models in production alongside our most strategic customers. You will own discovery, technical scoping, system design, build, and production rollout, partnering directly with customer engineering and domain teams. You will measure success through production adoption, measurable workflow impact, and eval-driven feedback that changes product and model roadmaps. You’ll work closely with our Product, Research, Partnerships, GRC, Security, and GTM teams. This role is based in Seoul. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. 50% travel is expected. In this role you will Own technical delivery across multiple deployments from first prototype to stable production. Build full-stack systems that deliver customer value and sharpen how we learn. Embed closely with customer teams, understand their needs, and guide adoption of what you build. Scope work, sequence delivery, and remove blockers early. Make trade-offs between scope, speed, and quality; adjust plans to protect delivery. Contribute directly in the code when progress or clarity depends on it. Codify working patterns into tools, playbooks, or building blocks that others can use. Share field feedback that helps Research and Product understand where the models succeed and where they can improve. Keep teams moving through clarity and follow-through. You might thrive in this role if you Bring 5+ years of engineering or technical deployment experience that includes customer-facing work. Have scoped and delivered complex systems in fast-moving or ambiguous environments. Write and review production-grade code across frontend and backend using Pytho

About the Team OpenAI's Training team is responsible for producing the large language models that power our research, our products, and ultimately bring us closer to AGI. Achieving this goal requires combining deep research into improving our current architecture and optimization techniques, alongside long-term bets aimed at improving the efficiency and capability of future generations of models. We are responsible for integrating these techniques and producing model artifacts used by the rest of the company, and ensuring that these models are world-class in every respect. About the Role As a member of the training team, you will push the frontier of LLM development for OpenAI's flagship models, enhancing intelligence, efficiency, and adding new capabilities. Relevant interests may include areas such as architecture design, long-context and efficient attention, optimization and the science of scaling. Ideal candidates have a deep understanding of LLM architectures, a sophisticated understanding of model inference, and a hands-on empirical approach. A good fit for this role will be equally happy coming up with a creative breakthrough, investing in strengthening a baseline, designing an eval, debugging a thorny regression, or tracking down a bottleneck. This role is based in London. 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: Design, prototype and scale up new architectures to improve model intelligence Execute and analyze experiments autonomously and collaboratively Study, debug, and optimize both model performance and computational performance Contribute to training and inference infrastructure You might thrive in this role if you: Have experience landing contributions to major LLM training runs Can thoroughly evaluate and improve deep learning architectures in a self-directed fashion Are motivated by safely deploying LLMs in the real world Are well-versed in the state of the a

About the Team OpenAI's mission is to ensure that artificial general intelligence benefits all of humanity. The Consumer Devices team is building a new generation of AI-powered products that seamlessly integrate hardware and software to create intuitive, transformative experiences. We bring together experts across embedded systems, machine learning, hardware, design, and product engineering to develop products at the intersection of AI and consumer technology. About the Role OpenAI is seeking a System Performance Engineer to profile, benchmark, and optimize performance across our embedded hardware products. In this role, you will work across operating systems, applications, camera and vision, graphics, and platform teams to define product KPIs, build performance tooling, and drive optimizations from early lab characterization through product launch and real-world usage. You will help establish the performance standards that shape the user experience of our products, ensuring they remain responsive, efficient, and reliable throughout their lifecycle. This role requires deep expertise in embedded or high-performance systems, strong operating systems fundamentals, and hands-on experience debugging under tight latency, power, and memory constraints. This role is based in San Francisco, CA. We use a hybrid work model of four days per week in the office and one day working remotely. Relocation assistance is available for new hires. In this role, you will: Develop system performance benchmarks, methodologies, and policies to evaluate end-to-end product behavior. Profile and analyze performance across key product use cases and workloads using custom and industry-standard profiling tools. Partner closely with engineering teams to identify bottlenecks and drive performance optimizations across the software stack. Define high-level product KPIs and establish measurement frameworks to measure launch readiness and monitor performance throughout the product lifecycle. Measure, re

About the Team OpenAI's mission is to ensure that artificial general intelligence benefits all of humanity. The Consumer Devices team is building a new generation of AI-powered products that seamlessly integrate hardware and software to create intuitive, transformative experiences. We bring together experts across embedded systems, machine learning, hardware, design, and product engineering to develop products at the intersection of AI and consumer technology. About the Role OpenAI is seeking a System Power Engineer to characterize, measure, and optimize power consumption across our embedded hardware products. In this role, you will work closely with Electrical Engineering and system software teams to build power test automation, measure subsystem-level power usage, and drive improvements that directly impact battery life, thermal behavior, charging performance, and system reliability. You will help establish the methodologies and metrics used to understand and improve power efficiency across real-world product experiences, from controlled lab environments to representative day-in-the-life usage scenarios. This role requires hands-on experience with embedded hardware platforms, power instrumentation, and the analysis of power profiles and system behavior. This role is based in San Francisco, CA. We use a hybrid work model of four days per week in the office and one day working remotely. Relocation assistance is available for new hires. In this role, you will: Define and develop power testing automation to evaluate system behavior across a range of workloads and operating conditions. Measure subsystem-level power consumption using power breakout probes and other lab instrumentation. Develop and execute power characterization tests spanning basic workloads, complex mixed-use scenarios, and representative day-of-use experiences. Partner closely with Electrical Engineers to identify opportunities to improve system power efficiency. Collaborate with software engineering

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About the team OpenAI’s Forward Deployed Engineering team partners with customers to turn research breakthroughs into production systems. We operate at the intersection of customer delivery and core platform development. About the role Forward Deployed Engineers (FDEs) lead complex end-to-end deployments of frontier models in production alongside our most strategic customers. You will own discovery, technical scoping, system design, build, and production rollout, partnering directly with customer engineering and domain teams. You will measure success through production adoption, measurable workflow impact, and eval-driven feedback that changes product and model roadmaps. You’ll work closely with our Product, Research, Partnerships, GRC, Security, and GTM teams. This role is based in San Francisco. We use a hybrid work model of 3 days in the office per week. We offer relocation assistance. Travel up to 50% is required. In this role you will Own technical delivery across multiple deployments from first prototype to stable production Build full-stack systems that deliver customer value and sharpen how we learn Embed closely with customer teams, understand their needs, and guide adoption of what you build Scope work, sequence delivery, and remove blockers early Make trade-offs between scope, speed, and quality; adjust plans to protect delivery Contribute directly in the code when progress or clarity depends on it Codify working patterns into tools, playbooks, or building blocks that others can use Share field feedback that helps Research and Product understand where the models succeed and where they can improve Keep teams moving through clarity and follow-through You might thrive in this role if you Bring 5+ years of engineering or technical deployment experience that includes customer-facing work Have scoped and delivered complex systems in fast-moving or ambiguous environments Write and review production-grade code across frontend and backend using Python, JavaScript,

About the Team Business Systems / Enterprise Platform Technology builds the internal systems, data foundations, workflow infrastructure, and enterprise platforms that help OpenAI operate at scale. The EPT AI Pod builds AI-native internal apps, MCP connectors, multi-agent workflows, and reusable platform capabilities across Finance, People, and GTM. About the Role As an Enterprise Applied AI Engineer, you will build internal apps for enterprise operations and the shared platform components those apps run on. This includes MCP connectors, multi-agent orchestration, data architecture, evals, monitoring, auditability, and governance. We’re looking for a hands-on engineer who is strong in Python, system design, enterprise integrations, data architecture, and applied AI systems. You should be excited to turn ambiguous business workflows into reliable internal products and shared infrastructure. In this role, you will: • Build internal apps for enterprise operations across Finance, People, and GTM • Build MCP connectors and enterprise integrations with strong auth, permissions, idempotency, retries, and rate-limit handling • Design end-to-end multi-agent workflows with tool routing, human approvals, audit trails, and safe action boundaries • Design data architecture for operational AI systems, including ingestion, schemas, quality checks, lineage, and governance • Build evals, monitoring, metrics, and regression tests for agentic workflows • Create reusable infrastructure, patterns, and components that other enterprise teams can build on • Partner with system owners and business owners to turn messy enterprise workflows into reliable internal products You might thrive in this role if you: • Have strong Python engineering skills for backend services, MCP connectors, agent/tool workflows, eval harnesses, and data ingestion jobs • Have strong system design skills across shared infrastructure, app architecture, reliability, and scaling • Have experience building internal apps,

About the team OpenAI’s Forward Deployed Engineering team partners with customers to turn research breakthroughs into production systems. We operate at the intersection of customer delivery and core platform development. About the role Forward Deployed Engineers (FDEs) lead complex end-to-end deployments of frontier models in production alongside our most strategic customers. You will own discovery, technical scoping, system design, build, and production rollout, partnering directly with customer engineering and domain teams. You will measure success through production adoption, measurable workflow impact, and eval-driven feedback that changes product and model roadmaps. You’ll work closely with our Product, Research, Partnerships, GRC, Security, and GTM teams. This role is based in NYC. We use a hybrid work model of 3 days in the office per week. We offer relocation assistance. Travel up to 50% is required. In this role you will Own technical delivery across multiple deployments from first prototype to stable production Build full-stack systems that deliver customer value and sharpen how we learn Embed closely with customer teams, understand their needs, and guide adoption of what you build Scope work, sequence delivery, and remove blockers early Make trade-offs between scope, speed, and quality; adjust plans to protect delivery Contribute directly in the code when progress or clarity depends on it Codify working patterns into tools, playbooks, or building blocks that others can use Share field feedback that helps Research and Product understand where the models succeed and where they can improve Keep teams moving through clarity and follow-through You might thrive in this role if you Bring 5+ years of engineering or technical deployment experience that includes customer-facing work Have scoped and delivered complex systems in fast-moving or ambiguous environments Write and review production-grade code across frontend and backend using Python, JavaScript, or compar

This role will support the fleet infrastructure team at OpenAI. The fleet team focuses on running the world’s largest, most reliable, and frictionless GPU fleet to support OpenAI’s general purpose model training and deployment. Work on this team ranges from Maximizing GPUs doing useful work by building user-friendly scheduling and quota systems Running a reliable and low maintenance platform by building push-button automation for kubernetes cluster provisioning and upgrades Supporting research workflows with service frameworks and deployment systems Ensuring fast model startup times though high performance snapshot delivery across blob storage down to hardware caching Much more! About the Role As an engineer within Fleet infrastructure, you will design, write, deploy, and operate infrastructure systems for model deployment and training on one of the world’s largest GPU fleet. The scale is immense, the timelines are tight, and the organization is moving fast; this is an opportunity to shape a critical system in support of OpenAI's mission to advance AI capabilities responsibly. 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: Design, implement and operate components of our compute fleet including job scheduling, cluster management, snapshot delivery, and CI/CD systems. Interface with researchers and product teams to understand workload requirements Collaborate with hardware, infrastructure, and business teams to provide a high utilization and high reliability service You might thrive in this role if you: Have experience with hyperscale compute systems Possess strong programming skills Have experience working in public clouds (especially Azure) Have experience working in Kubernetes Execution focused mentality paired with a rigorous focus on user requirements As a bonus, have an understanding of AI/ML workloads About OpenAI OpenAI is an AI resea