Agent Post Training Jobs

About the Team Codex is OpenAI's software engineering agent. Codex Security extends that work into one of the most important product areas in AI: helping organizations find, validate, prioritize, and fix real vulnerabilities in the software they build and depend on. The Codex Cyber team is building the product and platform foundations for AI-native application security. This includes Codex Security product experiences, cloud-based security analysis, platform controls across Codex, customer deployment and support tooling, and infrastructure that helps security researchers and cyber models improve over time. The team is early, small, and growing quickly, with a mandate to move fast and hire exceptional builders. About the Role We are looking for software engineers first: strong full-stack or product-minded generalists who can own ambiguous product and platform problems end to end. Security experience is helpful, and security curiosity is important, but this is not a role for security specialists who only occasionally write code. The right person is an excellent builder who is excited to work in security and can turn complex research, product, and customer needs into reliable systems. You will work across user-facing product surfaces, developer workflows, backend services, security analysis pipelines, cloud infrastructure, and internal tooling. You may build features that make Codex Security more useful for application security teams, systems that scale cloud-based security analysis, platform controls that make agentic coding safer, or infrastructure that helps security researchers and models become more effective. You will collaborate closely with engineering, product, security research, infrastructure, and customer-facing partners as Codex Cyber becomes a major product and platform investment for OpenAI. In this role, you will: Build end-to-end product features for Codex Security, from developer-facing interfaces to APIs, backend services, and workflow tooling. Own a

About the role There’s a wide gap between an agent that works in a demo and one that works across millions of live transactions. Closing it is the job. You’ll embed with the teams and customers who depend on AI — risk, fraud, collections, payments, support, developer experience — and design, build, and ship agentic systems into their production environments. You’ll also help build the platform underneath: Paytm’s AI inference platform (Pi) and the agentic runtime, orchestration, and tooling that lets agents reason, plan, use tools, and run multi-step workflows safely.

At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done. At Snowflake, we are building a high-impact team to help the world's most innovative companies unlock the power of AI. As a Senior Forward Deployed Engineer, Applied AI on our Cortex AI team, you will be a hands-on technical leader and trusted partner to our most strategic customers. You will own the end-to-end delivery of enterprise AI programs, leading a team of 2–4 engineers while staying deeply technical yourself. You will set the technical direction for your customer engagements, mentor your team, and serve as the senior technical voice at the intersection of product, engineering, and customer success. IN THIS ROLE AT SNOWFLAKE, YOU WILL: Lead Customer Programs : Own the full lifecycle of complex, multi-engineer AI engagements – from scoping and architecture through deployment, monitoring, and handoff. Be accountable for delivery quality and customer outcomes for the projects you lead. Own AI Quality : Define what "good" means for each engagement. Translate ambiguous customer goals into measurable quality metrics, evaluation frameworks, and golden datasets – then run systematic eval loops to hill-climb on agent quality, catch regressions before customers do, and continuously raise the bar on accuracy, faithfulness, and safety. Set the standard for how the team measures

Must be based in Vancouver The role We're hiring a dedicated data engineer to own the production data platform that our delivery, product, and engineering teams run on; designing integrated, governed data pipelines and delivering automated reporting, AI-assisted workflows, and predictive signals on top of them. You'll write production code, design systems, own CI/CD, and be accountable for the correctness of data that leaders make decisions on. What you'll do Design and operate our cloud data platform: ingestion, transformation, orchestration and serving. Integrate data from across the business (delivery tooling, CRM, product telemetry, finance, support and customer feedback systems) with shared identifiers, data contracts and lineage. Build automated and continuously refreshed reporting so teams manage by exception rather than chasing status. Connect approved AI agents to governed data with structured outputs, provenance, guardrails and human approval in the loop. Build feature pipelines and the MLOps controls behind predictive use cases: tests, versioning, promotion gates and drift monitoring. Own the engineering standards for data: testing, observability, environment promotion, PII classification and access control. What you'll bring Strong software engineering fundamentals: production-quality code, API and interface design, testing discipline, systems design. Real experience building and operating production data platforms on a cloud warehouse or lakehouse (Snowflake and AWS preferred) with dbt and a modern orchestrator. Practical AI tooling experience: something shipped, not prototyped. LLM-backed classification, extraction or structured-output pipelines; agent and tool-calling workflows; retrieval; evals. You can reaso

About the Team DoorDash’s GenAI Platform team sits within Machine Learning Platform and builds the shared infrastructure that helps DoorDash, Wolt, and Deliveroo teams safely bring GenAI-powered products, agents, automation, and personalization to production. Our mission is to increase the velocity of business impact from GenAI. A central pillar of that work is running frontier open-weight LLMs and VLMs (such as GLM, Qwen, Kimi, and DeepSeek) ourselves — real-time GPU serving, high-throughput batch inference, and fine-tuning on autoscaling GPUs — delivering large cost and latency wins (for example, a billion embeddings produced roughly 20× cheaper and visual models served roughly 72% cheaper). We also own core platform surfaces including the LLM Gateway, Agent Gateway, evals infrastructure, guardrails, and cost attribution. About the Role You will join a small, high-leverage team building production infrastructure for Generative AI at DoorDash, leading the design and architecture of our open-weights model platform spanning inference and fine-tuning: real-time GPU serving, high-throughput batch inference, and model fine-tuning. You’ll set technical direction across model serving and inference engines, fine-tuning and training pipelines, GPU autoscaling and utilization, batch pipelines, backend services, and observability, and mentor engineers as you go. This role is ideal for a senior engineer who enjoys owning ambiguous, high-impact systems and pushing the cost/performance frontier of GPU inference and fine-tuning in a fast-moving technical area where product needs, model capabilities, vendor ecosystems, and cost/performance tradeoffs are evolving quickly. You’re excited about this opportunity because you will… Lead the design of infrastructure that helps DoorDash teams move GenAI ideas from prototype to production, increasing the velocity of business impact from AI across the company. Own and evolve our open-weights serving stack — real-time GPU endpoints, high-thr

call center executive, also known as a contact center agent or customer service representative, is a frontline employee who acts as an intermediary between customers and a company. Their responsibilities include: Handling calls: Answering incoming and outgoing calls, and transferring them to the relevant department or agent Providing customer service: Addressing customer questions, concerns, and complaints Analyzing customer data: Conducting surveys to collect customer satisfaction data, and using that data to develop new strategies Communicating with customers: Using a variety of channels, including phone, email, social media, and chat Managing orders: Overseeing the timely delivery and payment of customer orders Recommending improvements: Suggesting improvements to systems and processes to increase efficiency call center BPO executive, also known as a customer care representative (CSR), is a frontline employee who deals with customer communication and support. Their responsibilities include: Answering customer queries and complaints Providing solutions to customer problems Ensuring customer satisfaction Building strong customer relationships Communicating with customers via calls, email, chat, and social media Processing orders, forms, and applications Providing information about products and services Processing returns

call center executive, also known as a call center representative or contact center agent, is a customer service professional who interacts with customers to help solve issues and provide information: Responsibilities Answer incoming calls, handle customer inquiries, and provide customer service support. They may also process payments, assist with orders, and address complaints. Skills Call center executives should have excellent communication and listening skills, and be able to analyze and solve customer problems. They should also be able to relate to customers from a variety of cultural backgrounds. Qualifications A high school diploma is usually required, and specific training may be an advantage. Other qualifications include attention to detail, time management, and a team player attitude.

About Pinterest: Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we’re on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product. Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other’s unique experiences and embrace the flexibility to do your best work. Creating a career you love? It’s Possible. At Pinterest, AI isn't just a feature, it's a powerful partner that augments our creativity and amplifies our impact, and we’re looking for candidates who are excited to be a part of that. To get a complete picture of your experience and abilities, we’ll explore your foundational skills and how you collaborate with AI. Through our interview process, what matters most is that you can always explain your approach, showing us not just what you know, but how you think. You can read more about our AI interview philosophy and how we use AI in our recruiting process here . About the Team: Hundreds of millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we’re on a mission to bring everyone the inspiration to create a life they love. Within Pinterest, the Pinterest Labs organization focuses on applied ML research and development to power the platform. Labs works across a broad variety of AI/ML initiatives, including LLMs/VLM, agent design, core computer vision, multimodal representation learning, visual generative modeling, recommender systems, graph learning, and more. This is the group that develops the foundation AI models that fully leverage the hundreds of billions of Pins and the associated knowledge graphs, and ships new product capabilities to fully utilize these technologies. We are curre

Who are we? Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems. We’re training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that. We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft. We are a global technology company headquartered in Toronto with key offices in London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul. Join us! Why this role? North is Cohere's cutting-edge AI workspace platform, designed to revolutionize the way enterprises utilize AI. It offers a secure and customizable environment, allowing companies to deploy AI while maintaining control over sensitive data. North integrates seamlessly with existing workflows, providing a trusted platform that connects AI agents with workplace tools and applications. Some of our most important work is making the agents and AI-powered experiences inside North genuinely useful in the workflows customers rely on every day. These systems become valuable when users can build with them, steer them, inspect their work, recover from errors, and trust them to complete messy tasks inside real enterprise environments. This role is about making those AI experiences reliable, useful, and production-ready. You’ll work with product engineering, modelling and design to turn model capability into reliable, user-facing systems: agent builders, eval frameworks, proactive intelligence, and new interfaces for collaborating with AI. Sometimes that means shipping a new product surface, sometimes a better eval or feedback

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

Strength in Trust OneTrust’s mission is to enable innovation through the responsible use of data and AI. We believe that ensuring data is trusted shouldn’t slow teams down—it should accelerate what’s possible. This led us to develop the first technology platform for responsible data use in 2016. Today, with AI representing the latest and most impactful expansion of data yet, OneTrust is once again redefining what responsible innovation looks like. OneTrust, the AI‑Ready Governance Platform™, unifies regulatory intelligence, automation, and connected governance workflows so businesses can continue to move at the speed of AI while ensuring good governance to prevent data misuse at scale. Trusted by thousands of organizations worldwide, OneTrust is shaping the future where trusted data becomes a transformative force for business and society. Strength in Trust OneTrust’s mission is to enable innovation through the responsible use of data and AI. We believe that ensuring data is trusted shouldn’t slow teams down—it should accelerate what’s possible. This led us to develop the first technology platform for responsible data use in 2016. Today, with AI representing the latest and most impactful expansion of data yet, OneTrust is once again redefining what responsible innovation looks like. OneTrust, the AI‑Ready Governance Platform™, unifies regulatory intelligence, automation, and connected governance workflows so businesses can continue to move at the speed of AI while ensuring good governance to prevent data misuse at scale. Trusted by thousands of organizations worldwide, OneTrust is shaping the future where trusted data becomes a transformative force for business and society. The Challenge As a Senior Staff Software Engineer on the AI Governance Engineering team, you will play a critical role in shaping and building OneTrust's next-generation AI Governance platform. You will help transform complex AI governance, compliance, safety, and agent r

Business Systems drives efficiency across Datadog through business process analysis, systems automation and integrations, AI agent and MCP development, and vendor/software review. The team is increasingly embedded in cross-functional initiatives across People, Finance, GTM , Legal, Recruiting, and Technical Solutions — translating ambiguous business problems into scoped, buildable solutions and owning delivery end-to-end. This is not a generalist BSA role. Each Senior BSA will own a cluster of business functions end-to-end, acting as an internal product manager for their domain rather than processing inbound requests reactively. There are two openings, each covering a different domain: People, Recruiting, Legal or Finance, GTM, Procurement As the role evolves alongside AI, Senior BSAs leverage agentic tools for data aggregation and context gathering while remaining the critical human-in-the-loop layer — owning business context and product outlook, validating use cases, managing stakeholder relationships, and making the judgment calls agents can't. At Datadog, we place value in our office culture - the relationships that it builds, the creativity it brings to the table, and the collaboration of being together. We operate as a hybrid workplace to ensure our employees can create a work-life harmony that best fits them. What You’ll Do: Discovery and scoping: Translate ambiguous asks from business stakeholders into well-defined requirements that Business Systems Engineers can build against. Many stakeholders don't know what they want or the cross-functional impact of what they're asking for — you surface both before engineering begins. Cross-functional visibility: Identify dependencies, downstream impacts, and integration considerations that requesting teams miss. Proactive opportunity identification: Develop deep domain knowledge to identify automation and AI opportunities before they become inbound requests, shifting the team from reactive in

Fin , now part of Salesforce, is on a mission to help businesses provide perfect customer experiences. Our AI Agent Fin is the highest-performing AI Customer Agent on the market today, enabling businesses to deliver impeccable, always-on customer support across the customer journey, from service, to sales, to ecommerce. Powered by our own AI models, Fin resolves complex customer issues end-to-end across every channel, with minimal set-up and integration. Fin can also be combined with our natively integrated Intercom help desk, giving modern support teams one single system. Together with Salesforce, the #1 AI CRM, where humans with agents drive customer success, we're building the future of customer experience. Here, ambition meets action. Tech meets trust. And innovation isn't a buzzword, it's a way of life. The world of work as we know it is changing, and we're looking for Trailblazers who are passionate about bettering business and the world through AI. Ready to level up your career at the company leading workforce transformation in the agentic era? You're in the right place. Agentforce is the future of AI, and you are the future of Salesforce. What's the opportunity? Implementation is an activity every Fin customer experiences, whether purchasing Fin for the first time, expanding Fin use to a new team, or adopting new features! As a Partner Services Manager at Fin, you’ll share ownership of this crucial process alongside our Service Delivery Partners. Your primary responsibility is ensuring customers implement Fin’s suite of AI tools to solve their most complex problems and ultimately drive incredible value for their business. Partner Services Managers have an outsized impact on the company. If you want to help make business personal for our customers and you want to work with an ever growing and changing team, you’re in the right place! What will I be doing? You will act as the Fin owner of partner-delivered services projects and the liaison who ensu