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About the Team The AI Architect team partners with organizations to turn OpenAI's most capable models into meaningful, real-world impact. We work with customers across industries and digital-native businesses to identify where AI can create value, design secure and scalable solutions, and help those solutions move from early exploration into sustained production adoption. The team brings together technical strategy, customer partnership, and practical deployment expertise, working closely with Sales, Product, Engineering, Research, and specialist delivery teams. About the Role As an AI Architect, you will be the senior technical owner for a named portfolio of customers and the primary technical counterpart to their leadership teams. You will act as the “CTO of your book of business”, shaping each customer's AI strategy and guiding their journey from pre-sales discovery and solution evaluation through deployment, adoption, and measurable business impact. You will own the technical account plan across ChatGPT Enterprise, the OpenAI API, Codex, and other agentic AI solutions. In partnership with the Account Director, you will translate business priorities into a focused use-case portfolio, an actionable adoption roadmap, and a clear path to durable customer value and growth. The Account Director owns commercial strategy; you own the technical strategy, customer journey, and path to production value. You will remain accountable for the technical outcome while bringing in the right specialists across deployment, implementation, enablement, security, product, and partners to provide deeper expertise and execute work where needed. This role calls for strong industry fluency, sound architectural judgment, and the ability to move confidently between executive strategy and hands-on technical conversations. In this role, you will: Serve as the primary technical advisor and long-term technical relationship owner for a named portfolio of existing customers and pre-sales prospects. Partner with Account Directors on account strategy while owning the technical account plan, technical milestones, adoption priorities, and expansion opportunities. Lead discovery with executives and technical teams to identify, qualify, and prioritize use cases tied to meaningful business outcomes. Develop clear Applied AI Architectures spanning models, applications, data, integration, security, privacy, governance, evaluation, and deployment. Guide customers through technical evaluations, demonstrations, workshops, prototypes, and proofs of value, securing confidence in both the solution and its path to production. Maintain a focused use-case portfolio with clear decision criteria, ownership, blockers, success measures, delivery needs, and adoption plans. Develop trusted relationships and technical champions across CTOs, CIOs, CISOs, AI leaders, engineering teams, and other customer stakeholders. Qualify and coordinate support from Deployment Engineering, implementation, training and enablement, product and domain specialists, partners, and other delivery teams. Remain accountable for technical progress and customer outcomes while ensuring delivery teams own implementation execution once engaged. Track adoption, usage, account health, production readiness, and measurable customer impact, intervening early when risks threaten value realization. Apply industry or digital-native expertise to recognize repeatable patterns, sharpen customer priorities, and identify relevant expansion opportunities. Share customer insights with Product, Engineering, and Research, translating field learnings into better products, architecture guidance, and reusable practices. You might thrive in this role if you: Have significant experience in customer-facing technical roles such as solutions architecture, solutions engineering, technical account leadership, AI deployment, or technical customer success. Have guided enterprise organizations from technical evaluation through production adoption and measurable business impact. Build credibility with senior technical and business leaders while communicating equally well with hands-on engineers. Bring strong software and cloud architecture foundations, including APIs, distributed systems, data integration, identity, security, and privacy. Understand modern AI systems, frontier LLM models, agentic applications, model evaluation, retrieval, or enterprise AI workflows. Can prototype, explain technical tradeoffs, and work confidently with APIs, SDKs, and languages such as Python or JavaScript. Exercise sound judgment about when to go deep personally, when to involve specialists, and how to define clear handoffs and ownership. Have experience developing technical account plans, prioritizing complex customer portfolios, and connecting adoption to measurable outcomes. Bring meaningful expertise in a relevant industry or strong fluency with the needs of digital-native businesses. Communicate clearly and can turn ambiguity into a practical technical narrative, executive decision, or action plan. Work collaboratively across disciplines and care deeply about helping organizations deploy advanced AI responsibly. About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement . Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. In addition, job duties require access to secure and protected information technology systems and related data security obligations. To notify OpenAI that you believe this job posting is non-compliant, please submit a report through this form . No response will be provided to inquiries unrelated to job posting compliance. We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made via this link . OpenAI Global Applicant Privacy Policy At OpenAI, we believe artificial intelligence has the potential to help people solve immense global challenges, and we want the upside of AI to be widely shared. Join us in shaping the future of technology.
Who We Are Notion is the collaborative AI workspace where teams and agents think together . We're building one place where your knowledge, projects, meetings, and AI tools live side by side, so work is faster, clearer, and less fragmented. Millions of individuals, small teams, and large companies run their work on Notion. Notinos (our employees) are customer zero in bringing this future of work to life. We care about craft, building things that last, and the belief that great work is still fundamentally human. Our goal isn’t to ship the next feature. Each and every team of Notinos is working to set the standard for how humans work together in the AI era. From building a business’s system of record to making and managing AI agents to automating away the busy work, we care deeply about giving our customers more time for their life’s work. About The Role As a Forward Deployed Engineer on Notion’s Services team, you will lead the hands on technical delivery of our most complex customer engagements. You will design, build, and deploy production ready solutions that help enterprise customers integrate Notion as the operating layer for their business. You’ll embed with enterprise customers to design and build solutions that integrate Notion deeply into their technical and operational environments. This includes writing and maintaining custom code, designing and deploying production-grade custom agents and AI workflows with MCP, Agent APIs, and Notion’s automation and execution infrastructure, building data pipelines and resolving complex challenges around scale, permissions, and governance. You’ll embed with enterprise customers to design and build solutions that integrate Notion deeply into their technical and operational environments. This is a customer-facing engineering role for someone who is comfortable writing code, debugging technical issues, explaining tradeoffs to stakeholders, and turning ambiguous customer problems into scalable technical solutions. Your work will help shape best practices for how we support complex customer needs and ensure Notion’s platform is ready for scale. What You'll Achieve Own the hands-on technical delivery of customer engagements, including deep technical discovery, requirements gathering, solution design, and end to end implementation. Act as a trusted technical advisor, helping customers make informed architectural decisions and identify opportunities to expand and deepen their use of Notion. Design, build, and operate custom agents, integrations, automations, and data pipelines that connect Notion with customers’ systems and workflows. Lead the design and execution of large-scale content and data migrations, including discovery, scoping, data modeling, transformation logic, validation, and post-migration optimization. Work directly with customer engineering, IT, security and business stakeholders to gather technical requirements, identify constraints, evaluate feasibility, and make sound architectural decisions that maximizes the value of Notion within their broader technical ecosystem. Troubleshoot complex implementation issues across APIs, integrations, automation logic, data quality, permissions, authentication, system limits, and customer specific environments. Design and operate feedback loops with Product, CX, and Engineering, translating real-world implementation challenges into actionable insights, technical requirements, and tooling improvements that directly influence Notion’s Product Roadmap and our Customers. Build reusable technical assets, including migration tooling, integration patterns, reference implementations, discovery frameworks, technical standards, scripts, and internal delivery tooling. Help define how Services delivers complex technical implementations at scale by improving methodologies, scoping artifacts, build patterns, technical documentation and engineering best practices. Skills You'll Need to Bring 5+ years of experience in customer-facing or forward deployed engineering role or a similar hands-on technical role. Proficiency in at least one programming language such as Java, JavaScript, Node.js, SQL, or Python and comfort with writing production-quality code in customer-facing or internal engineering contexts. Hands-on experience with APIs and data integration. Ability to lead technical discovery with customers, assess feasibility, identify risks, scope technical work, estimate effort, and translate ambiguous requirements into an executable plan. Strong debugging and problem-solving skills, with the ability to isolate root causes across code, APIs, permissions, integrations and customer specific configuration. Strong written and verbal communication skills, with the ability to engage both technical and business audiences effectively. A track record of delivering customer value by translating technical challenges into solutions that drive outcomes for customers at scale. Nice to Haves Experience working in professional services, preferably in a startup or high-growth environment. Experience deploying AI agents autonomously in complex coding or business workflows. Experience designing or implementing AI-powered workflows, including work with MCPs, APIs, LLM applications, prompt engineering, retrieval/RAG systems or workflow orchestration. Background in developing technical frameworks, discovery methodologies, or internal tooling from the ground up. Experience with ETL/ELT workflows, data transformation, schema mapping, validation scripts, or large-scale content migration tooling. Strong history of collaboration with product and engineering teams, including influencing roadmaps or architectural decisions. Experience supporting pre-sales or early engagement phases, including technical discovery, migration scoping, feasibility analysis, effort estimation, and building prototypes or custom scripts to validate approaches. Strong track record of successful enterprise customer implementations. Notion is committed to providing highly competitive cash compensation, equity, and benefits. The compensation offered for this role will be based on multiple factors such as location, the role’s scope and complexity, and the candidate’s experience and expertise, and may vary from the range provided below. For roles based in San Francisco or New York City, the estimated range for total on target earnings (including base salary and on target incentive pay) for this role is $175,000 - $240,000 per year. By clicking “Submit Application”, I understand and agree that Notion and its affiliates and subsidiaries will collect and process my information in accordance with Notion’s Global Recruiting Privacy Policy and NYLL 144 . #LI-Onsite A Note on AI You don’t need deep AI expertise for every role, but we do expect every Notino to be intellectually curious, drawn to tinkering and discovery, and excited to use AI as a real collaborator in their work. For some roles, AI fluency is a core requirement — when that’s the case, we'll say so explicitly in the qualifications. People who thrive here don’t treat AI as a novelty. They use it to think better, and make their work easier for others to build on. Equal Opportunity & Accommodations We hire talented people from a wide range of backgrounds. If you’re excited about this role but don’t meet every bullet, we still encourage you to apply. Notion is an equal opportunity employer and does not discriminate on the basis of any legally protected characteristic. Consistent with applicable law, we will consider for employment qualified applicants with arrest and conviction records. Notion provides reasonable accommodations during the application process; if you need one, please let your recruiter know. Notion is proud to be an equal opportunity employer. We do not discriminate in hiring or any employment decision based on race, color, religion, national origin, age, sex (including pregnancy, childbirth, or related medical conditions), marital status, ancestry, physical or mental disability, genetic information, veteran status, gender identity or expression, sexual orientation, or other applicable legally protected characteristic. Notion considers qualified applicants with criminal histories, consistent with applicable federal, state and local law. Notion is also committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures. If you need assistance or an accommodation due to a disability, please let your recruiter know.
About the Team The Codex Research team creates the frontier agents OpenAI ships to the world. We are training the models behind our agents in Codex, ChatGPT, the API, and other frontier products: persistent, proactive intelligence that can operate computers, collaborate with people and other agents, and expand what people and organizations can imagine, attempt, and achieve. We define what the next generation of agents should be able to do, build the training signal that teaches those abilities, and run the experiments that make them real. Our work spans coding, tool use, computer use, multi-agent coordination, long-horizon execution, factuality, instruction following, calibrated reasoning, and taste. Our team is where new model capabilities get made. We build the data, environments, graders, training methods, and feedback loops that shape what OpenAI's next agents can do, then carry those capabilities through major training runs and into the products people use. About the Role As a member of the Codex Research team, you will improve the capabilities, reliability, and product fit of OpenAI's agentic models. You might own a research direction, build the infrastructure that makes large training runs faster and more trustworthy, create evals that reveal where models fail, or drive a capability from an idea through experimentation, integration, and launch. This role is intentionally broad. The strongest candidates are not defined by one method or subfield; they are people who can take an ambiguous capability problem and make progress across research, engineering, data, evals, and product. You should be excited to work on models that act in the world: writing and debugging code, using tools, calling functions, operating computers, collaborating with other agents, and completing valuable work on behalf of users. You will work with researchers, engineers, product teams, infrastructure teams, and safety/alignment partners to decide what should go into major model runs, measure whether it worked, and ship improvements into products used by real people. This is a high-agency role for people who want their work to land directly in frontier models. In this role, you might: Design and run experiments that improve agentic model behavior across coding, tool use, function calling, computer use, multi-agent collaboration, long-horizon tasks, factuality, instruction following, and calibrated reasoning. Own end-to-end improvements to the post-training stack, including RL, data pipelines, graders, reward signals, evals, diagnostics, and model-behavior analysis. Build evals and environments that expose the next set of model failures, then turn those failures into training data, product fixes, or new research directions. Partner with Codex, API/platform, ChatGPT, and general-agent product teams to understand what users need and translate product signal into model improvements. Work on early-training and alignment interventions, including data mixtures, objectives, synthetic data, and eval loops that shape downstream agent behavior. Help decide which integrations, capabilities, and fixes are ready for inclusion in major model runs. Improve the machinery for large-scale training and launch: experiment velocity, reliability, observability, reproducibility, cost, latency, and production readiness. Take on cross-functional projects that touch model training, product infrastructure, and the production agent harness, such as multi-agent systems or training directly against production-like environments. Debug hard failures in shipped or near-shipped models and turn messy qualitative behavior into concrete hypotheses, experiments, and fixes. You might thrive in this role if you: Have strong technical fundamentals in machine learning, software engineering, systems, statistics, or a related field, and can learn quickly across the parts you have not worked in before. Have hands-on experience with LLMs, RL, RLHF/RLAIF, post-training, evals, graders, synthetic data, model training, coding agents, tool-using agents, or production ML systems. Are excited by open-ended problems where the path is unclear, the signal is noisy, and the right answer requires both research taste and engineering execution. Care about product impact and model behavior, not just benchmark movement. You have opinions about what makes an agent useful, reliable, honest, tasteful, and easy to work with. Can move from a vague behavioral problem to a concrete experiment: define the hypothesis, build the pipeline, run the model, analyze the result, and decide what to do next. Are comfortable working across research, product, infrastructure, data, evals, and safety boundaries, and can communicate clearly with each group. Like building load-bearing systems and processes when that is what the team needs, even if the work is not glamorous. Want to train and ship the models that make agents genuinely useful for developers, enterprises, researchers, and everyday users. About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement . Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. In addition, job duties require access to secure and protected information technology systems and related data security obligations. To notify OpenAI that you believe this job posting is non-compliant, please submit a report through this form . No response will be provided to inquiries unrelated to job posting compliance. We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made via this link . OpenAI Global Applicant Privacy Policy At OpenAI, we believe artificial intelligence has the potential to help people solve immense global challenges, and we want the upside of AI to be widely shared. Join us in shaping the future of technology.