Ai Workflow Engineer Latam in San Francisco

About the Team OpenAI’s API Multicloud team is responsible for extending OpenAI’s API platform into strategic cloud environments, starting with AWS . The team’s mission is to distribute OpenAI’s API broadly and safely by enabling key API technologies in cloud-native environments, in close partnership with Amazon and internal teams across Codex, Research, Safety Systems, and Applied. The team is focused on bringing core developer and enterprise capabilities into cloud-native environments, including cloud-hosted Codex, model customization / post-training as a service, and new stateful runtime environments for agentic workloads. This work sits at the intersection of production ML systems, developer platforms, model behavior, and large-scale infrastructure. About the Role We’re looking for a backend engineer who can quickly understand OpenAI’s models, products, and systems, then adapt first-party deployments for other cloud platforms. You’ll build backend services, APIs, SDK integrations, authentication flows, and cloud service infrastructure that let developers use OpenAI capabilities in the cloud environments where they already build. This role involves working across teams, sometimes embedded with partner product groups, to ship products quickly and across multiple platforms at the same time. It’s a strong fit for engineers who have built developer tools, especially AI-powered tools, communicate clearly across technical boundaries, and can shape architectures that support different deployment models; experience building cloud services is a strong plus. In this role, you will: Build backend and infrastructure systems that extend OpenAI’s API platform into cloud-native environments, like AWS. Design and ship cloud-contained products that allow customers to use OpenAI capabilities while keeping workloads and data within cloud environments. Help stand up cloud-hosted Codex experiences powered by the OpenAI Responses API. Build the infrastructure and runtime abstractions

About the Team OpenAI’s mission is to ensure that general-purpose artificial intelligence benefits all of humanity. We believe our research will eventually lead to artificial general intelligence, a system that can solve human-level problems. The social team helps bring OpenAI’s work to people around the world, translating complex ideas into clear, accessible, and timely content and stories across platforms. The team supports OpenAI’s mission by helping people understand how to use AI in practical, meaningful ways, while clearly and authentically communicating our technology, values, and approach to safely building powerful AI. About the Role Do you want to be one of the people behind the @ChatGPT handle on Linkedin? We’re looking for a smart and accomplished Social Media Manager (IC) to drive and manage long-tail evergreen educational social content primarily around OpenAI products on Linkedin and YouTube from the @ChatGPT and @OpenAI accounts. This role sits at the intersection of AI, education, product storytelling, and social media. You'll help shape how people around the world understand and adopt one of the fastest-growing technologies in history. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week. In this role, you will Work closely with cross-functional teams to brief and create evergreen content related to OpenAI products like ChatGPT and Codex Craft and execute social strategy and content to encourage and sustain product adoption Partner with product, marketing, and creative teams to develop educational social content that helps people understand and adopt OpenAI products. Monitor and report on product usage trends and conversations across social Balance the requests of many teams while ensuring content goes out accurately and on time Synthesize and communicate complex topics in clear language tailored for different audiences You might thrive in this role if you 7+ years of professional experience in social

About the Team The GTM Data Science team partners with Go-to-Market, Technical Success, Product, Engineering, RevOps, and Strategic Finance to build the shared intelligence layer for OpenAI's B2B business. The team turns product usage, customer behavior, revenue, field activity, and customer feedback into rigorous insight products that help leaders and field teams understand where customers are succeeding, where adoption is blocked, and what actions will accelerate durable growth. We are building systems that make customer intelligence proactive: surfacing risk, expansion potential, product gaps, and repeatable playbooks before they show up as escalations or missed opportunities. About the Role As the Applied Data Science & Insights Lead for GTM Intelligence Solutions and Technical Success, you will be a hands-on technical leader responsible for shaping how OpenAI measures, understands, and improves customer adoption across our B2B products. You will build AI/ML-powered intelligence products that connect account health, product usage, customer lifecycle, support tier, qualitative sentiment, commercial context, and field actions into a practical operating system for GTM and Technical Success. This role will build the data science foundation for Technical Success: defining the metrics, models, operating insights, and decision systems that help the team scale customer adoption and expansion with rigor. You will also be expected to build and lead a small mighty team over time: setting direction, hiring and developing talent, creating operating cadences, and holding a high bar for technical rigor and business impact. You will lead the development of models, metrics, and decision systems that recommend what GTM and Technical Success teams should do next, explain why, and measure whether those interventions worked. Your work will help customers move from pilots to production, deepen usage across products, identify high-value use cases, reduce churn risk, and create a f

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 OpenAI’s Financial Engineering and Identity data science team owns how revenue flows through our products and builds the systems that enable people and organizations to access OpenAI products safely, seamlessly, and at global scale. Identity sits at the critical intersection of growth, trust, and user experience. The team owns the experiences and infrastructure behind sign up, sign in, account recovery, authentication, and identity integrations across both consumer and enterprise products. As OpenAI expands across products and markets, Identity plays an increasingly important role in helping more users get started quickly while protecting them from abuse, fraud, and account compromise. About the Role We're looking for the first dedicated Data Scientist to partner with the Identity organization. In this role, you will define how we measure success across the entire identity journey—from first-time sign up and onboarding through authentication, account recovery, and enterprise identity experiences. You'll develop the experimentation frameworks, metrics, and analytical approaches that guide product decisions while helping the team navigate one of Identity's core challenges: optimizing growth while maintaining trust and security. You'll work closely with Product, Engineering, Design, Abuse, Risk, and Go-to-Market teams to identify opportunities, quantify trade-offs, and influence strategy. Some questions can be answered through A/B tests. Others require observational analyses, causal inference, and judgment under uncertainty. This is an opportunity to shape the analytical foundations of a high-impact product area from the ground up. This role is based in San Francisco, CA. We use a hybrid model (3 days/week in office) and offer relocation support. In this role, you will Define the north-star metrics and measurement frameworks used to evaluate the identity experience across consumer and enterprise products. Design and analyze experiments to optimize top-of

About the Team Security is at the foundation of OpenAI's mission to ensure that artificial general intelligence benefits all of humanity. The Identity Infrastructure Engineering team sits at the core of this effort, designing and building the identity and access management solutions that protect model weights, customer data, and critical systems across multiple cloud environments. The team partners across OpenAI, including Applied Engineering, Research, IT, Security, Infrastructure, and Engineering, to provide secure and scalable platforms for identity, access management, permissioning, orchestration, and safe AI research. About the Role We’re looking for an engineering leader to lead Identity Infrastructure Engineering, the team building the systems that govern and scale access across OpenAI’s research, engineering, and internal platforms. This role sits at the center of cloud infrastructure, identity, software engineering, and security-critical operations. You’ll lead engineers building control planes, policy systems, workload and agent authorization patterns, infrastructure-as-code, and operational foundations that help OpenAI move quickly while keeping access reliable, auditable, least-privileged, and safe under failure. The ideal candidate has led teams responsible for large-scale, mission-critical infrastructure. They can go deep into code and architecture when needed, while giving engineers and technical leads the clarity and ownership to do their best work. They set technical direction, grow strong teams, make durable architecture decisions, and turn ambiguous 0-to-1 problems into platforms OpenAI can trust and build on for years. In this role, you will: Build and lead a high-performing Identity Infrastructure team, going deep enough technically to set direction while empowering the team to own delivery. Define the strategy for identity platform as the policy plane for access across people, agents, workloads, services, clouds, and internal systems. Scale Acc

About the team The Agent Post-Training 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 researcher working on Frontier Evals & Environments, you will help build north star model environments to drive progress towards safe AGI/ASI. Your work will directly guide the research programs of the most ambitious training runs happening at OpenAI. Some prior open-sourced evaluations built by researchers in this role include GDPval , SWE-bench Verified , MLE-bench , PaperBench , and SWE-Lancer . If you are interested in feeling firsthand the fast progress of our models, and steering them towards good outcomes, this is the role for you. 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'll: Create ambitious RL environments to push our models to their limits, and measure frontier

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

By applying to this role, you will be considered for Research Scientist roles across all teams at OpenAI. About the Role As a Research Scientist here, you will develop innovative machine learning techniques and advance the research agenda of the team you work on, while also collaborating with peers across the organization. We are looking for people who want to discover simple, generalizable ideas that work well even at large scale, and form part of a broader research vision that unifies the entire company. We expect you to: Have a track record of coming up with new ideas or improving upon existing ideas in machine learning, demonstrated by accomplishments such as first author publications or projects Possess the ability to own and pursue a research agenda, including choosing impactful research problems and autonomously carrying out long-running projects Be excited about OpenAI’s approach to research Nice to have: Interested in and thoughtful about the impacts of AI technology Past experience in creating high-performance implementations of deep learning algorithms 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

About the Team The Agent Post-Training 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 Agent Post-Training, 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, meas

About the Team The Agent Post-Training 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 researcher working on Frontier Evals & Environments, you will help build north star model environments to drive progress towards safe AGI/ASI. Your work will directly guide the research programs of the most ambitious training runs happening at OpenAI. Some prior open-sourced evaluations built by researchers in this role include GDPval , SWE-bench Verified , MLE-bench , PaperBench , and SWE-Lancer . If you are interested in feeling firsthand the fast progress of our models, and steering them towards good outcomes, this is the role for you. 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 Create ambitious RL environments to push our models to their limits, and measure frontie

About the Team The Agent Post-Training 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 builds the data, environments, graders, training methods, and feedback loops that shape what OpenAI’s next agents can do and what they are like to work with, then carries those improvements through major training runs and into products used by people every day. About the Role As a member of the Agent Post-training Personality team, you will help make OpenAI’s agents exceptional collaborators. You will study what makes an agent thoughtful, clear, perceptive, appropriately proactive, and genuinely easy to work with, then translate those insights into evals, training data, reward signals, and model improvements. We use “personality” to mean much more than writing style or general likability. It includes whether an agent understands what the user is trying to accomplish, communicates with good judgment, adapts to context, asks useful questions, handles disagreement honestly and takes initiative at the right moments. The goal is to create a strong, tasteful default that can adapt to different people and situations. This work combines behavioral research, product thinking, research and communication taste. You will collaborate with product teams, human experts, and researchers across post-training and pretraining to ensure that improvements survive the full trai

About the Team Security is at the foundation of OpenAI’s mission to ensure that artificial general intelligence benefits all of humanity. The Security team protects OpenAI’s technology, people, and products. We are technical in what we build but are operational in how we do our work, and are committed to supporting all products and research at OpenAI. Our Security team tenets include: prioritizing for impact, enabling researchers, preparing for future transformative technologies, and engaging a robust security culture. About the Role As a Security Engineer, Application Security you will be responsible for identifying and mitigating security vulnerabilities within software applications through building security tools, code reviews, penetration testing, and security assessments. We’re looking for people who will work closely with development teams to ensure secure coding practices are integrated throughout the software development lifecycle, preventing security risks before they emerge. You will also provide security guidance to developers and other stakeholders, fostering a culture of security awareness within the organization. The role is preferred to be based in San Francisco, Seattle or New York City but may consider remote work. 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: Perform Security Assessments : Conduct regular security assessments, code reviews, and penetration testing to identify vulnerabilities in applications and software. Develop and Implement Security Tools : Design, develop, and implement security tools, frameworks, and methodologies to protect applications against security threats. Collaborate with Development Teams : Work closely with development teams to ensure security best practices are integrated throughout the software development lifecycle (SDLC), including secure coding guidelines. Threat Modeling and Risk Assessment : Conduct threat modeling and risk

About the Team The Agent Post-Training 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 We believe that the final enabler for AGI is spending compute on context. As a Context Researcher on Agent Post-Training, you will scale compute spent on context. You will get to work in our frontier training stack on enabling the next paradigm of model training with a clear product interface for iterative deployment (Codex Chronicle). 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 scaling of compute on context. 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,

About the Team OpenAI’s Strategic Finance organization provides financial insights and guidance to support the company’s long-term strategy and ambitious growth. We partner across Product, Partnerships, Engineering, and GTM to allocate resources to the highest-impact opportunities while protecting sustainable unit economics. The Applications Technology Strategic Finance team partners closely with Product to scale core offerings and bring new products to market. We lead revenue forecasting and performance management across the product portfolio, including economic margins, pricing, and partnership deal pricing and structuring. About the Role We are hiring on our Strategic Finance Partnerships team to drive strategic decision-making across OpenAI’s growth and media partnership portfolio, focused on our consumer business. This role will be a critical finance partner to Partnerships deal leads and Product owners, responsible for evaluating, pricing, and structuring partnerships, and translating partner opportunity into decision-ready economics and performance management. The role will be hands-on in deal evaluation, negotiation support, and portfolio oversight. You will shape how OpenAI approaches partnership unit economics, measurement and incrementality, and how partnership performance is incorporated into forecasts and planning. This role is based in San Francisco, CA, with a hybrid work model (3 days/week in-office). Relocation assistance is available. In this role, you will: Own financial evaluation for growth and media partnerships, including modeling revenue, margin, compute, and payback to support decision-making and negotiations. Develop clear economic frameworks and deal guardrails (pricing floors, rev-share structures, caps, minimum guarantees, performance-based terms) to protect long-term unit economics. Partner closely with Product and Partnerships to define and measure incrementality and ensure contract terms align with measurable outcomes. Lead partnershi