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Surface Treatment Glebar 1 in United States

356 active opportunities · Updated October 2026

Explore current surface treatment glebar 1 jobs across United States. Filter by work mode, employment type, experience, department, date posted and distance.

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📍 United States· Full-time
✓ High-confidence listingCompany trend -100%

$960K – $1.4M/yr

Quick readStrong listing-quality and freshness signals

👋 Welcome to Glide! At Glide we’re reimagining the banking experience for the modern world . Our embedded fintech platform empowers legacy financial institutions, like community banks and credit unions, to pioneer novel digital experiences for their customers. You’ll be joining an all-star team with engineering, product, and growth experience from Stripe, Google, and Amazon. We’re looking for a talented Digital Support Manager (DSM) to help us grow our product to hundreds of banks. We’re bringing a new perspective to the decades-old financial world , and we’re hoping you can help us do that! Your Responsibilities: Serve as the primary point of contact for clients post go-live support, managing inbound support requests and ensuring timely, high-quality resolutions Leverage deep knowledge of financial institution operations to diagnose issues at the root cause level — not just the surface Partner with clients to understand their regulatory environment, core system configurations, and operational workflows in order to recommend solutions that truly fit their needs Maintain accurate records of all client interactions, escalating issues to engineering or product teams as needed Identify patterns in support requests and proactively surface product feedback and client insights to internal teams Leverage AI tools to streamline and optimize day-to-day responsibilities Contribute to the development of help articles, training materials, and client-facing documentation Need-to-Haves: Experience working at a bank or credit union — you know what a core system is, you understand regulatory requirements, and you can speak your clients' language A natural curiosity to dig past the surface-level problem and uncover what clients actually need Strong written and verbal communication skills with a client-first mindset Ability to manage multiple open issues simultaneously without dropping the ball Comfort working in a fast-paced, early-stage startup environment where the playbook is sti

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📍 United States· Full-time
✓ Quality checkedCompany trend -100%

ABOUT THE TEAM Mural’s Admin & Security portfolio owns the experiences that let organizations adopt, govern, and measure the value of Mural at enterprise scale. The portfolio spans three domains: Admin & Identity Management, Enterprise Security, & Customer Insights. This role leads Customer Insights and supercharges it into a surface that turns Mural’s product data into the narratives that drive renewals, fund expansion, and prove the ROI of collaboration to Admins and buyers. YOUR MISSION Own the Customer Insights product area end-to-end. Build the user facing experiences and the data foundation to turn raw data into shared, clear, and actionable narratives. Define Mural’s POV on what AI-native insights look like as the category shifts from static dashboards to proactive, conversational, agentic interfaces. You’ll work across three layers in parallel: The canonical usage data layer: This is the foundation that powers Company Insights today and needs to be deliberately built and enriched so other surfaces such as engagement, growth, AI, can consume it tomorrow. The customer-facing surface: This is how the data is presented in-product, whether it’s on an insights page, a dashboard, scheduled and ad hoc reporting, audit logs, or APIs that can be consumed by Admins, end users, execs, and Mural teams. The AI-native expansion: How Mural incorporates natural language queries, agentic workflows, and proactive analytics to evolve and extend the insights surface. WHAT YOU'LL DO Own product strategy, roadmap, and execution for Customer Insights from data model through customer-facing experience Define the usage data layer in partnership with Engineering and Data including the metrics that anchor renewal and expansion narratives Evolve customer-accessible audit logs to be enterprise ready Define Mural's POV on AI-native insights and ship the first set of AI-powered capabilities on this surface Partner with Sales and Customer Success to translate insights into the n

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📍 San Francisco, California, United States· Full-time
✓ Quality checkedCompany trend -80.6%

About Sentry Software runs the world and the pace is faster than ever. Sentry helps developers fix errors and performance issues before users notice, so teams can spend less time firefighting and more time building. Trusted by 200,000+ organizations, Sentry is today’s application monitoring standard and our team is building its AI-native future. About the role Issue Workflow is Sentry's primary product surface. Our issue platform processes billions events daily and turns them into actionable insights that help millions of developers fix bugs faster. As a Staff Software Engineer on the Issue Workflow team, you'll architect the systems that power this experience. You'll work at the intersection of high-scale distributed systems and product engineering, building real-time data pipelines, search backends, and analysis systems that surface signal from noise. This is product engineering at massive scale—where every architectural decision impacts millions of debugging sessions. You'll be the technical leader who shapes how Sentry groups issues, how we make search lightning-fast, how we enable sophisticated agentic workflows, and how we ensure that the product is performant even at billions-of-events scale. Your work will define what's possible for the most trafficked part of Sentry's platform. In this role you will Drive technical strategy and roadmap. Partner with engineering leadership, product, and design to shape the multi-quarter technical vision for Issue Workflow platform. Make strategic calls about architectural direction, technology choices, and technical debt. Ensure the team is building a strong foundation to scale with Sentry's growth. Solve complex performance and scalability challenges. Champion product quality and user experience. Build features that don't just work—they delight. You understand that milliseconds matter in the developer experience. You sweat the details of interfaces, error messages, loading states, and edge cases. You instrument everything s

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📍 United States· Full-time
✓ Quality checkedCompany trend -100%

At Linear, we're building the product development system for teams and agents. AI is fundamentally changing how software gets built, and we’re shaping the tools this new era requires. Founded in 2019, Linear has become the platform of choice for more than 40,000 companies (including OpenAI, Coinbase, and Ramp) to plan, build, and ship their products. Today, our team is distributed across North America, Europe, and Australia, and we’re continuing to grow internationally. What unites us is relentless focus, fast execution, and a deep care for software craftsmanship. As Linear moves upmarket, the gap between deal close and successful enterprise rollout has become our most important surface area. We're hiring an Implementation Manager to own that gap. You will be the single point of accountability from signed contract through successful go-live, coordinating across CSM, Solutions Engineering, Customer Education, Sales, and the customer's own teams to make every enterprise rollout repeatable, on time, and high quality. Location & work mode Linear is a remote-first company, with optional co-working offices in San Francisco, New York, and London. This role is open to candidates based in North America. EST time zone is preferred for this position. We value deep focus and async collaboration, with intentional moments to connect in person through team off-sites, optional co-working, and occasional travel. What you'll do Own end-to-end implementation plans for enterprise customers: timeline, milestones, dependencies, risk, and stakeholder accountability Run the handoff from Sales at deal close in partnership with Customer Success and Solutions Engineering: validate services scope, timeline commitments, complexity signals, and migration readiness Coordinate workspace architecture, migration, and integration workstreams (SSO/SCIM, Slack, GitHub, Jira sync, custom integrations) across customer IT, Solutions Engineering, and engineering escalations Build the enablement calenda

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📍 New York, NY, United States· Full-time
✓ High-confidence listingCompany trend -99.2%

From $120K/yr

Quick readStrong listing-quality and freshness signals

About Ramp Ramp is building the smart infrastructure for finance teams, embedded in the transaction flow of every dollar a business spends. We automate how over $200B in annualized spend flows in and out of 70,000+ companies: authorizing payments, flagging risk, categorizing spend, and closing books. The problems are high-stakes, data-dense, and unforgiving. We hire people with high agency and high urgency. We look for slope over intercept. We care less about where you trained and more about what you’ve built. At Ramp, everyone is a builder who owns problems end to end and makes consequential decisions that shape the outcome. The median Ramp customer saves 5% and grows revenue 16% in their first year – far in excess of businesses operating without Ramp. We believe every ambitious company deserves the same. If you want to build systems that directly shape how companies move and manage billions, Ramp is the place to do it. About the Role As a Product Designer at Ramp, you are accountable for outcomes, not just artifacts. You work with PMs, engineers, and other designers to define the right problems, explore and validate solutions, and ship product experiences that change customer behavior. Design at Ramp is AI first and builder led. Work starts in an LLM, moves into tools like Claude and Cursor to explore flows and interactions, and then comes into Figma for systems and polish. Designers prototype early, test with real customers, and stay involved through launch and iteration. We are looking for multiple product designers who are excited to work this way and who want to use AI as a core part of how they design. What You’ll Do Own product work end to end: Partner with PM and engineering to define problems, explore solution spaces, validate concepts, and ship product improvements that move key metrics. Stay involved through launch and iteration, not just handoff. Start in an LLM: Use tools like Claude to clarify intent, draft short PRDs, and surface risks, edge cases, a

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📍 Foster City, California, United States· Full-time
✓ Quality checkedCompany trend -87.5%

Replit is the agentic software creation platform that enables anyone to build applications using natural language. With millions of users worldwide, Replit is democratizing software development by removing traditional barriers to application creation. The AI Studio is the team responsible for designing, building, and operationalizing internal software platforms across every functional department of the company, including People Operations, Customer Support, Sales, Marketing, Finance, Recruiting, and Executive Operations. We treat each internal department as its own product surface, and in truth as its own startup, with its own customers, its own metrics, and its own reasons for existing. We ship custom software, built on Replit’s own platform, to solve operational problems that off-the-shelf SaaS tools cannot serve well at our scale and pace of growth. Position Summary The Member of Technical Staff (AI Builder) is a full-time builder role with substantial autonomy. You will design, architect, and ship AI-powered internal platforms that run the operations of the company across many departments at once. This is not a role for someone who wants a narrow, well-defined lane. It is a role for someone who wants to walk into an ambiguous business problem, understand it well enough to argue about it with the department lead, and then ship the software that fixes it. We are looking for people who genuinely understand the mechanics of a business: how revenue is actually made, why recruiting velocity matters, what makes support scale or break, how finance closes a month, and why each department is critical to whether the company wins or loses. You do not need to have run every function, but you need to respect why each one exists and be able to reason about it like an operator, not just an engineer. Because we treat each department as its own startup, we strongly favor people who have either run their own business or worked on a fast-scaling startup. You know what it feels like

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📍 Foster City, California, United States· Full-time
✓ Quality checkedCompany trend -87.5%

Replit is the agentic software creation platform that enables anyone to build applications using natural language. With millions of users worldwide, Replit is democratizing software development by removing traditional barriers to application creation. Replit is a software creation platform that enables anyone to build applications using natural language. With millions of users worldwide, Replit helps more people build and ship software. About the Team Product Platform builds and owns the shared foundations the rest of Replit is built on: backend infrastructure, connectors, product primitives, and the frontend platform. When these foundations are solid, every other team moves faster. This role goes deep on the frontend platform: the architecture and platform layer behind every core product surface. The work is high-leverage and horizontal, and gives you exposure across the whole of engineering. We are a small, collaborative team that values curiosity and clear thinking over pedigree, and we care more about how you reason and build than the route you took to get here. If you like making other engineers faster, you will fit in here. About The Role As a Product Engineer focusing on the frontend platform , you will own the frontend architecture behind core product experiences: application frameworks, the API and data layer, testing infrastructure, and client performance. The goal is simple: product teams ship quickly and reliably on what you build. The team’s work is guided by a few simple questions: Is our core frontend architecture (frameworks, state, routing, SSR/CSR) sound, consistent, and easy to build on? Is our API and data layer reliable and ergonomic, with clear contracts, sensible error handling, and effective caching? Are user-facing surfaces fast and well-instrumented, with testing infrastructure that keeps them safe to change? Is the codebase easy to navigate, change, and extend, including for AI coding agents? You’ll partner closely with engineering, produc

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📍 San Francisco, California, United States· Full-time
✓ Quality checkedCompany trend -73.5%

We believe that the way people interact with their finances will drastically improve in the next few years. We’re dedicated to empowering this transformation by building the tools and experiences that thousands of developers use to create their own products. Plaid powers the tools millions of people rely on to live a healthier financial life. We work with thousands of companies like Venmo, SoFi, several of the Fortune 500, and many of the largest banks to make it easy for people to connect their financial accounts to the apps and services they want to use. Plaid’s network covers 12,000 financial institutions across the US, Canada, UK and Europe. Founded in 2013, the company is headquartered in San Francisco with offices in New York, Washington D.C., London and Amsterdam. Team: Plaid is becoming an AI-first company, and Intelligent Tooling builds internal platforms and tools to lead the transformation. Our biggest opportunity isn't just better tools for engineers, it's extending AI-native internal tooling to the rest of Plaid. Tools built for engineers assume things non-engineers don't have: local toolchains, monorepos, engineer credentials, PR-based workflows. That mismatch means Ops, Support, and other teams can't easily inherit what we build for engineering. They need their own path and we're building that path. Role: As a Senior Software Engineer on Intelligent Tooling, you will build and operate internal systems that empower non engineering teams to automate their workflows with AI. You will own the product and platform layer for internal tools, including the constraints and infrastructure that keep those tools safe and maintainable. There's no existing playbook for this at Plaid. You will define what the right non-eng AI surface looks like, ship its first durable versions, and partner closely with internal users to make sure it solves real problems. You will act as the engineering point of contact embedded with non-engineering teams, running discovery and trans

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📍 New York, New York, United States· Full-time
✓ High-confidence listingCompany trend -87.8%

From $139K/yr

Quick readStrong listing-quality and freshness signals

Reports to: Head of Developer Growth · New York, NY NOTE: This is not a traditional marketing role, it's a growth role that reports into the Product org. We're hiring someone to build our developer audience the way the best consumer brands build audiences, with a real voice, a point of view, and the speed to act on both. You'll own where and how we show up in the places developers actually spend time, run our developer social channels, expand into new ones, and build the tooling and measurement behind it. This is a builder role, not simply a coordination role. What You'll Do: Own the voice, editorial standard, and publishing cadence for Datadog's developer channels (@datadogdevs on X, Datadog Developers on LinkedIn) Treat replies as a primary surface. The best accounts win in the mentions, not the feed Expand into the places developers actually spend time: Reddit, YouTube, Discord, Bluesky, dev.to, Hacker News, and whatever you make the case for. Always openly as Datadog — developers catch anything else immediately, and you only get caught once Turn shipped engineering work into things people want to read and watch. Releases, changelogs, war stories, the occasional postmortem that deserves a wider audience Build the attribution model connecting what you publish to trials and signups. Nobody is handing you this one Run real experiments: a hypothesis, a readout, and the willingness to kill something publicly when it doesn't work Lead the developer content engine around events Get other people posting — Datadog engineers under their own names, and developers outside the company who already like us and could use the support Track what developers are saying about us and our competitors, and route it back to product and growth Who You Are: You've grown an audience from a small number to a large one You can point to outcomes your content moved, not just reach You're a strong writer with a distinctive voice, and you know the difference between writing about an audience and

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📍 Massachusetts, New York, United States· Full-time
✓ High-confidence listingCompany trend -87.8%

From $192K/yr

Quick readStrong listing-quality and freshness signals

Senior Product Manager - Search Datadog’s Search team helps users – both human and agents – find answers to their questions. Search is a critical function in Datadog, and touches many product surfaces: the query editors in product homepages and dashboards, search bars for finding relevant assets, the global cmd+k navigation search, and the MCP tools that our Bits AI agent uses to respond to natural language prompts. Search is a full-stack team: owning user-facing search components, backend search ranking systems, and machine learning models to produce recommendations. The Search team is relatively new, and still growing. We have recently built out agentic search tools, and we are looking for a leader to help us expand to ambitious orchestration systems that deliver accurate results, and proactive recommendations across both keyword and semantic search. Beyond this, you’ll have room to influence how Datadog thinks about Search as a strategic surface. What you’ll do: Define and deliver how Datadog's AI agents discover the right context and tools to answer natural-language questions accurately and at scale Stay on top of industry trends in UI and agentic search experiences and capabilities Collaborate with Applied AI teams to integrate ranking, personalization, and recommendation models that scale across both human and agentic users Define and monitor KPIs for search quality, adoption, and downstream impact on user productivity; use them to drive data-informed decision making Engage directly with customers and internal product teams to deeply understand search journeys across query editors, global navigation, and natural-language agent interfaces Who you are: You have experience with search, ranking, or recommendation systems You are familiar with or very interested in MCP servers and differences between human and agentic UX You have a sharp eye for design and strong opinions on the micro-interactions — keyboard navigation, autocomplete behavior, loading

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📍 San Francisco, United States· Full-time
✓ High-confidence listingCompany trend -98.9%

From $232K/yr

Quick readStrong listing-quality and freshness signals

Airbnb was born in 2007 when two hosts welcomed three guests to their San Francisco home, and has since grown to over 5 million hosts who have welcomed over 2 billion guest arrivals in almost every country across the globe. Every day, hosts offer unique stays and experiences that make it possible for guests to connect with communities in a more authentic way. The Community You Will Join: The Relevance & Personalization (R&P) team is Airbnb's matching intelligence engine — a talented team of ML engineers, applied researchers, and technical program managers who connect guests to the right listings across every surface and help hosts compete and thrive in our marketplace. We work at the intersection of search ranking, recommendations, personalization, and generative AI, and we're building toward a future where Airbnb feels less like a search engine and more like a knowledgeable travel companion that understands your needs across your entire trip journey. The Difference You Will Make: As Product Manager for Relevance & Personalization, you will help set the strategy and drive execution for some of Airbnb's highest-leverage AI systems. You'll own the roadmap and shape how personalization works across the guest journey, and help define how we close the feedback loop for hosts. You'll partner with engineers, researchers, designers, and cross-functional teams to ship systems that directly drive bookings, guest satisfaction, and host success — at global scale. A Typical Day: Define and drive the roadmap for Airbnb's relevance and personalization platform — from natural language query understanding to multi-turn, context-aware discovery experiences Make prioritization calls that balance multiple competing objectives: guest experience, host success, revenue, fairness, and marketplace health Partner with ML engineers and applied researchers to shape model strategy, evaluation frameworks, and experimentation design Align cross-functional partners — Guest, Host,

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Relocation support. Relocation assistance is stated. This does not establish visa sponsorship.
📍 San Francisco, California, United States· Full-time
✓ Quality checkedCompany trend -83.9%

About the Team The Early Access Program (EAP) team leads high-impact alpha programs at the intersection of customers, Product, Research, Engineering, GTM, Security, Legal, and launch teams. We partner with customers to test emerging capabilities with real-world use cases, surface actionable insights, and support launch decisions. Our team is made up of builders who learn quickly, collaborate deeply, create clarity in ambiguity, communicate openly, and iterate constantly. About the Role We’re hiring an Early Access Deployment Engineer to lead technical engagements with customers who are leveraging our frontier capabilities to solve real-world use cases. You will work at the earliest—and often messiest—stage of development, when capabilities are still unclear, tooling and processes are evolving, and the path from promising technology to a valuable real-world application has yet to be defined. You will be a hands-on builder, problem solver, and technical partner to customers and our research/product team. You’ll push beyond initial assumptions, identify high-value use cases, prototype solutions, design useful evaluations, and troubleshoot what is and is not working. Managing multiple customer engagements at once, you will help customers navigate ambiguity and difficult technical decisions while translating their experience into clear, actionable feedback for Research and Product. You will also own the end-to-end execution of early access programs—from onboarding customers, supporting live experimentation, synthesizing findings, and informing launch decisions. You’ll collaborate deeply with Research, Product, Engineering, Applied Evals, GTM, Legal, Security, Marketing, and other launch partners to create clarity, manage risk, and keep programs moving through changing conditions. Success in this role means turning frontier capabilities into real-world customer value and high-quality research signals. You will develop reusable technical approaches from early deployments,

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Relocation support. Relocation assistance is stated. This does not establish visa sponsorship.
📍 San Francisco, California, United States· Full-time
✓ Quality checkedCompany trend -83.9%

About the Team The CoT Monitorability team at OpenAI studies whether and when the chain-of-thought of frontier reasoning models is monitorable enough to support scalable oversight. We study how to measure monitorability , which training mechanisms affect monitorability, and speculative methods to improve monitorability. While we mostly focus on CoT monitorability at the moment, we care more generally about any form of monitorability, auditing methods, and improving alignment. We were the first to show that chain-of-thought monitoring can be a practical additional safety mechanism, and today our monitoring systems are actively used on OpenAI’s largest RL training runs to detect misbehavior. The issues we surface are then used to help improve our reward functions, environments, etc (without directly training against a CoT monitor). Our work sits in Alignment and intersects with model training, alignment evaluations, monitoring, and frontier-risk research.We care most about monitorability where the stakes are high, and about preserving useful oversight signals as models become more capable. About the Role We’re looking for a researcher with strong empirical ML expertise and a deep interest in model behavior, alignment, or interpretability. Direct chain-of-thought interpretability experience is welcome but not required; strong candidates may come from broader interpretability, alignment, model training, or investigative model-behavior work. As a researcher on the Alignment team, you will design and run experiments that improve our understanding of model monitorability. You will investigate how training interventions across the model-development pipeline influence whether reasoning remains legible, build evaluations that make those questions measurable, and help translate findings into practical oversight and training recommendations. You may also help develop new monitoring models or methods and apply them to OpenAI’s largest training runs. This role is especially well

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📍 San Francisco, California, United States· Full-time
✓ Quality checkedCompany trend -83.9%

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 OpenAI is seeking to build an investigative capability for Secure Manufacturing & Stealth programs. The risk surface for unreleased products, prototypes, confidential hardware, infrastructure, supply chain, manufacturing, and launch-readiness efforts spans employees, vendors, suppliers, logistics partners, physical movement of assets, procurement records, manufacturing workflows, access systems, device telemetry, and adversarial collection. This role is intended to build and run investigations across that specialized environment. In this role, you will: Lead complex SMS investigations to proactively identify and mitigate risks to unreleased products, prototypes, confidential hardware, secure manufacturing programs, and launch-readiness efforts. Investigate unauthorized disclosure, suspected leaks, insider risk, supplier compromise, vendor misconduct, theft, diversion, tampering, counterfeiting, surveillance, adversarial collection, and suspicious activity involving sensitive programs. Connect digital evidence, physical access activity, supply chain records, manufacturing data, vendor behavior, employee activity, collaboration metadata, procurement records, shipping data, and OSINT into clear findings and risk-reduction actions. Conduct proactive threat hunting to surface early indicators of compromise, collection, leakage, or insider activity affecting sensitive programs. Develop investigative playbooks, evidence-handling standards,

AWSGitRestAI
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📍 San Francisco, California, United States· Full-time
✓ Quality checkedCompany trend -83.9%

About the Team OpenAI's research training infrastructure powers how our frontier models are trained and evaluated. The Simulation team sits at the intersection between the agentic harness that powers OpenAI's products and the research infrastructure where GPT-next is trained, ensuring that our model's training environment is as realistic as possible. This team owns the integration layer that connects our production harness capabilities into the training stack. The work is highly cross-functional and high leverage: researchers depend on it to run experiments and evaluations reliably as well as to develop the next generation of harness capabilities. Failures in this surface can materially affect training velocity and correctness. About the Role We're looking for a Principal Software Engineer to lead the architecture and evolution of the Simulation Platform. You'll own a critical interface between research and engineering, building the systems, APIs, and operational patterns that let researchers use agentic coding infrastructure safely and effectively in training environments. This role is ideal for a senior backend or infrastructure engineer with strong technical judgment, product sense for highly technical users, and the ability to drive execution across multiple teams. The highest-leverage work is building robust infrastructure that supports and accelerates research without compromising engineering quality. In this role, you will Design, build, and evolve the integration between the Codex harness that powers OpenAI's products and research training infrastructure used for training GPT-next Build a platform for our LLMs to train and be evaluated in simulated environments that mimic their deployment setting as closely as possible, on every axis: agentic harness, compute substrate, timing, tools, data sources, humans in the loop, and more Own major integration surfaces end-to-end, from architecture and API design through rollout, operations, and long-term maintenance Bu

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