Agent Post Training Jobs

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 our evaluation platform — the unified evals backbone that lets teams measure, trace, and trust the quality of LLM and agent systems across the company, powering trace/score ingestion, LLM-as-judge workflows, agent simulations, and LLM observability for the tens of millions of daily requests flowing through our LLM Gateway. We also own core platform surfaces including the Agent Gateway, open-weights model serving and batch inference, guardrails, and cost attribution. About the Role You will join a small, high-leverage team building production infrastructure for Generative AI at DoorDash, with a primary focus on our evals and LLM observability platform: the systems that let teams evaluate, trace, and continuously improve the quality of LLM and agent products. You’ll work across evaluation frameworks and SDKs, OpenTelemetry-based trace/score ingestion, LLM-as-judge and offline/online eval pipelines, agent simulations, data pipelines, backend services, and observability. This role is ideal for an engineer who enjoys building reliable measurement and quality primitives in a fast-moving technical area where product needs, model capabilities, vendor ecosystems, and evaluation methodologies are evolving quickly. You’re excited about this opportunity because you will… Build the infrastructure that helps DoorDash teams move GenAI ideas from prototype to production, increasing the velocity of business impact from AI across the company. Work on our unified evals platform — evaluation SDKs, OpenTelemetry trace/score ingestion, LLM-as-judge, offline and online eval pipelines, and agent simulations — alongside the LLM Gatew

We are investing in agentic AI and need a Senior AI Engineer to lead the design and delivery of these systems. This is a foundational hire: you will own both the agent-facing workstreams — pipelines, orchestration, conversational interfaces — and the underlying context layer that makes them reliable, including memory management, knowledge graph integration, and retrieval infrastructure. You will work closely with data engineers, project leads, and client stakeholders, and play a key role in shaping how Lynx builds and ships AI solutions at scale. What This Involves: Lead the architecture and delivery of agentic AI systems end-to-end: agents, orchestration, tool use, and multi-step reasoning workflows. Own the context layer: design and implement memory architectures (episodic, semantic, working memory) and integrate GraphRAG and knowledge graph retrieval into agentic pipelines. Build robust RAG systems — including vector retrieval, graph traversal, and hybrid search — and ensure retrieval quality through evaluation frameworks. Translate client requirements into technical designs, presenting approaches and trade-offs to both technical and non-technical stakeholders. Define standards and reusable patterns for agentic AI development that other engineers at Lynx can build on. Set up observability, evaluation, and monitoring pipelines to ensure AI systems perform correctly in production. Requirements: 5–8 years of software or ML engineering experience, with at least 2–3 years building LLM-based or agentic AI systems in production. Deep hands-on experience with agentic frameworks (LangChain, LlamaIndex, AutoGen, CrewAI, or similar) and LLM APIs (OpenAI, Anthropic, etc.). Strong understanding of agent design patterns: ReAct, planning loops, tool use, multi-agent coordination, and memory architectures. Practical experience with GraphRAG or knowledge graph-based retrieval (e.g., Neo4j, Microsoft GraphRAG) and vector databases (Pinecone, Weaviate, Qdrant, etc.). Proficiency in

About AlphaSense: The world’s most sophisticated companies rely on AlphaSense to remove uncertainty from decision-making. With market intelligence and search built on proven AI, AlphaSense delivers insights that matter from content you can trust. Our universe of public and private content includes equity research, company filings, event transcripts, expert calls, news, trade journals, and clients’ own research content. The acquisition of Tegus by AlphaSense in 2024 advances our shared mission to empower professionals to make smarter decisions through AI-driven market intelligence. Together, AlphaSense and Tegus will accelerate growth, innovation, and content expansion, with complementary product and content capabilities that enable users to unearth even more comprehensive insights from thousands of content sets. Our platform is trusted by over 6,000 enterprise customers, including a majority of the S&P 500. Founded in 2011, AlphaSense is headquartered in New York City with more than 2,000 employees across the globe and offices in the U.S., U.K., Finland, India, Singapore, Canada, and Ireland. Come join us! About the Role We are building an AI Security and Governance capability and need an AI Security Analyst to be the front line for detecting, investigating, and containing risk across every AI tool, agent, and model touching AlphaSense's environment. You will monitor enterprise AI usage end to end, hunt for unauthorized ("shadow") AI and rogue agent activity, and turn raw AI telemetry into triaged findings the security and governance team can act on. Working alongside the Automation Engineer, Data Analyst, and Director, you will be a primary contributor to the evidence base underpinning our ISO 42001 certification and our broader AI risk posture. Key Responsibilities AI Tool Discovery & Shadow AI Monitoring Continuously monitor CASB/SWG, OAuth, and endpoint telemetry to discover unsanctioned AI tools, browser extensions, and API-level agents in u

As a Senior Software Engineer on Coder’s Agentic Engineering team, you’ll build and evolve the systems behind our agentic development experience. You’ll work across the agent harness, integrations, and workflows that connect agents with real development environments. You’ll stay hands-on, solve complex technical problems, and work closely with Product, Design, and other engineers to ship reliable agentic experiences. What you’ll do here Design and build production systems in Go, with work across React and TypeScript where needed. Improve agent execution, tool use, context management, streaming, and long-running workflows. Extend our provider-agnostic architecture as models and capabilities change. Build reliable integrations between agents, workspaces, tools, and developer infrastructure. Own projects from implementation through rollout and iteration. Contribute to design reviews, code reviews, and technical discussions. Partner with Product and Design to turn agent capabilities into useful developer experiences. Improve the reliability, performance, and operability of agentic systems. What we’re looking for Strong experience building and operating production software systems. Hands-on experience with Go. Experience with React and TypeScript. Experience building systems around LLMs or agentic workflows. Familiarity with model APIs, tool calling, context management, or agent loops. Good understanding of distributed systems and production reliability. Working knowledge of AWS. Strong problem-solving skills and comfort working through technical ambiguity. Someone who contributes beyond their own code through reviews, collaboration, and knowledge sharing. Bonus tacos if you have Experience building coding agents, developer tools, or cloud development environments. Experience with MCP, agent tools, or multi-agent systems. Experience with remote execution, sandboxing, or isolated compute. Experience building integrations across multiple model providers. Experience with AW

As a Senior Software Engineer on Coder’s Agentic Engineering team, you’ll build and evolve the systems behind our agentic development experience. You’ll work across the agent harness, integrations, and workflows that connect agents with real development environments. You’ll stay hands-on, solve complex technical problems, and work closely with Product, Design, and other engineers to ship reliable agentic experiences. To provide substantive overlap with the team, this position must be in Eastern Time. What you’ll do here Design and build production systems in Go, with work across React and TypeScript where needed. Improve agent execution, tool use, context management, streaming, and long-running workflows. Extend our provider-agnostic architecture as models and capabilities change. Build reliable integrations between agents, workspaces, tools, and developer infrastructure. Own projects from implementation through rollout and iteration. Contribute to design reviews, code reviews, and technical discussions. Partner with Product and Design to turn agent capabilities into useful developer experiences. Improve the reliability, performance, and operability of agentic systems. What we’re looking for Strong experience building and operating production software systems. Hands-on experience with Go. Experience with React and TypeScript. Experience building systems around LLMs or agentic workflows. Familiarity with model APIs, tool calling, context management, or agent loops. Good understanding of distributed systems and production reliability. Working knowledge of AWS. Strong problem-solving skills and comfort working through technical ambiguity. Someone who contributes beyond their own code through reviews, collaboration, and knowledge sharing. Bonus tacos if you have Experience building coding agents, developer tools, or cloud development environments. Experience with MCP, agent tools, or multi-agent systems. Experience with remote execution, sandboxing, or isolated compute.

Become a part of our caring community The Lead Software Engineer codes software applications based on business requirements. The Lead Software Engineer works on problems of diverse scope and complexity ranging from moderate to substantial. The Lead Software Engineer standardizes the quality assurance procedure for software. Oversees testing and debugging and develops fixes. Researches complaints and makes necessary adjustments and/or recommendations to resolve complex software related issues. Advises executives to develop functional strategies (often segment specific) on matters of significance. Exercises independent judgment and decision making on complex issues regarding job duties and related tasks, and works under minimal supervision, Uses independent judgment requiring analysis of variable factors and determining the best course of action. Key Responsibilities Technical Architecture and Ownership:** Design and own the end-to-end architecture of Centerwell's AI systems, including LLM-powered clinical tools, RAG pipelines, harnesses, agent-based workflows, and intelligent automation. Make and communicate foundational technical decisions in close collaboration with the broader engineering team. Model Development and Fine-Tuning:** Evaluate, select, and where appropriate guide the fine-tuning of foundation models. Establish model evaluation frameworks that prioritize safety, accuracy, and clinical relevance. Clinical and Product Partnership:** Collaborate closely with product managers, designers, clinicians, and data stakeholders to understand care delivery workflows and translate them into well-scoped, high-impact AI features. HIPAA Compliance and Responsible AI:** Ensure all AI systems are designed, deployed, and monitored in compliance with HIPAA and Humana's Responsible AI standards, including participation i

About the Role & Team Agentic Amplitude is the team that’s responsible for Amplitude's AI agent strategy. The team shipped the Amplitude Global Agent, Custom agents, and our MCP surface, and continues to deliver new products at a fast pace. The team is small, moves fast and thrives on curiosity, autonomy, and strong cross-functional partnership. We operate with a bias toward rapid iteration and refine our approach as the underlying technology and models advance. This role is the product lead for this surface area. The successful candidate will set the strategy and vision and lead the design and engineering teams to deliver new innovations, while serving as the company’s thought leader on agentic products. Responsibilities Define the direction for Amplitude's agents and MCP surfaces over the next 12 to 24 months, and determine the priorities that will guide investment. Own the product vision for how AI agents help our customers to get to insights faster, make decisions with greater confidence, and take the right actions to improve their products. Advance our MCP capabilities so that customers can work with Amplitude from their coding agent, CLI, or IDE, in addition to our own user interface. Create the evals, quality standards, and feedback mechanisms required to measure customer value and iterate on the agent experience. Talk regularly with customers to understand their workflows and identify new opportunities and use cases for AI agents to deliver value. Partner closely with the field organization to enable them to position, demo, and support AI Agent products effectively. Serve as a thought leader on agentic products, establishing best practices both internally and with customers. Measures of Success A clear and inspiring agent and MCP strategy that leadership and the field organization can articulate consistently. Increased adoption of existing agents and MCP capabilities, complemented by new agentic products that address emerging customer needs. Broad MCP ad

Every day, tens of millions of people come to Roblox to explore, create, play, learn, and connect with friends in 3D immersive digital experiences– all created by our global community of developers and creators. At Roblox, we’re building the tools and platform that empower our community to bring any experience that they can imagine to life. Our vision is to reimagine the way people come together, from anywhere in the world, and on any device. We’re on a mission to connect a billion people with optimism and civility, and looking for amazing talent to help us get there. A career at Roblox means you’ll be working to shape the future of human interaction, solving unique technical challenges at scale, and helping to create safer, more civil shared experiences for everyone. We are seeking a highly motivated Senior Analyst to own and evolve a best-in-class tooling ecosystem that powers Roblox's Safety, Privacy, Trust & Safety, and Support Operations teams. In this role, you will sit at the intersection of operations and technology — driving systematic improvements, scaling tooling infrastructure, and ensuring agents across global vendor sites have the tools they need to operate efficiently and safely at Roblox's scale. You will join a growing team of administrators, incident managers, and product support specialists in India, providing comprehensive tooling and admin support to our global operations teams. You will help build a premier suite of agent tooling by managing systematic changes, identifying improvements, and delivering exceptional service to our internal customers. You will Administer and configure applications — including Zendesk, Absorb, JIRA, and other third-party and internally developed tools — to support 24/7 operations across multiple vendor sites. Design and implement queue and routing systems that reduce agent decision fatigue, enable quality support interactions, and support seamless multi-site operations. Analyze and translate b

As a Staff Software Engineer on Coder’s Agentic Engineering team, you’ll shape the systems behind our agentic development experience. You’ll work across the agent harness, integrations, and workflows that connect agents with real development environments. You’ll stay hands-on while setting the team's technical direction. You’ll lead complex work, make sound architectural decisions, and help other engineers do their best work. What you’ll do here Set technical direction across Coder’s agent harness, integrations, and workflows. Design and build production systems in Go, with work across React and TypeScript where needed. Evolve agent execution, tool use, context management, streaming, and long-running workflows. Extend our provider-agnostic architecture as models and capabilities change. Lead complex projects from early ambiguity through production. Raise the engineering bar through design reviews, code reviews, and technical mentorship. Partner with Product and Design on clear, useful agent experiences. Improve the reliability, performance, and operability of agentic systems. What we’re looking for Deep experience building and operating production software systems. Strong hands-on experience with Go. Experience with React and TypeScript. Hands-on experience building systems around LLMs and agentic workflows. Experience with model APIs, tool calling, context management, or agent loops. Strong distributed systems knowledge. Working knowledge of AWS. A track record of setting technical direction without formal authority. Strong architectural judgment and comfort working through ambiguity. Someone who makes the engineers around them better. Our tech stack Backend: Go, Postgres Frontend: TypeScript, React Infrastructure: AWS, Kubernetes Observability: Prometheus, Grafana CI/CD: GitHub Actions Bonus tacos if you have (Tacos? If you need an ice-breaker, ask how we say thanks by giving tacos!) Experience building coding agents, developer tools, or cloud development environm

About the Team OpenAI's Enterprise team builds AI-powered enterprise products and shared platform capabilities that help organizations put advanced AI to work securely and at scale. Our work spans enterprise workflows, agent experiences, integrations, identity, administration, security, governance, and deployment. About the Role As a Technical Program Manager on Enterprise, you will lead the technical strategy and execution behind the products and shared capabilities that make ChatGPT, Codex, and future OpenAI products useful, secure, and scalable for organizations. You will translate customer needs, competitive dynamics, and product priorities into actionable plans, influence architectural direction, and deliver durable capabilities across application, platform, and infrastructure layers. The role requires deep technical fluency, strong product judgment, and the ability to move between hands-on execution and broader enterprise strategy. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. In this role, you will: Drive technical strategy and execution for enterprise product and AI workflow initiatives, from design through implementation, launch, customer rollout, and iteration. Partner with engineering teams to influence architectural direction, interface definitions, and implementation tradeoffs across full-stack products, APIs, integrations, and shared platform systems. Translate enterprise customer requirements into actionable product priorities across AI-powered workflows, agent experiences, integrations, permissions, data access, evaluations, identity, security, governance, and deployment readiness. Represent the needs of enterprise buyers, IT administrators, security teams, business leaders, developers, and end users in product and technical decisions. Identify adoption barriers, competitive gaps, and opportunities to make OpenAI products easier for organizations

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! Role Overview: Building AI agents that can assist with any kind of enterprise work is a challenging, open-ended problem. One key piece of solving it is replicating real work environments as realistically as possible - filling them with hard tasks to solve, creating plausible input data, and defining clear rewards for completing the work the right way. We build many of these reinforcement learning (RL) environments, then drop our agents into them to evaluate or train them. In this role, you are responsible for creating these RL environments, running AI agents inside them, and improving both the agents and the environments in the process. The results reach customers, whose feedback feeds back in - and the agent/environment improvement loop continues. Key Responsibilities: There are many open problems in this space. As a Member of Technical Staff, RL Environments, you will: Build new RL environments targeting different agentic capabilities and industry areas Train and evaluate agents in those environments Make all the pieces work together: tasks, data, tool implementations, and verifiers Work across modeling and product to identify

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 building the world’s most accessible AI coding agent. Replit Agent can be used by anybody to bring their ideas to life. Whether it’s an app for yourself, the next great startup idea, or a tool to make you more productive at work, Replit Agent can help build it. Replit builds complete apps better than anybody thanks to our full suite of services that handle app integrations, storage, hosting, analytics, and more. We don’t just build apps in development, we handle the full lifecycle into production and beyond. About the role: Help power the development of Replit Agent as a technical leader for the Replit Cloud organization. You will report to the Vice President of Engineering. The Replit Cloud team builds Replit’s first party cloud infrastructure so users can build, scale, and succeed entirely on Replit. They manage databases, application storage, app publishing and hosting, development/production environment splitting, custom domains, and more. By having a set of first party services that integrate seamlessly, you will power one of Replit’s key product differentiators. You will: Help lead major projects, either by taking new products from 0->1 or doubling down on our first party primitives to keep winning users. Work closely with designers and product managers, to quickly iterate on Replit Cloud to continually grow and improve the product. Identify the hardest technical and/or quality problems holding us back, and then build solutions. Mentor and develop new senior engineers to help grow the team. Ship product and build infrastructure as a true full stack builder using: TypeScript, React, CSS, Postgres, Go, and Terraform. Examples of what you could do: Leverage our unique cloud infrastructure to build diffe

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. About the role: Help power the development of Replit Agent as an engineer in the Replit Cloud organization. The Replit Cloud team builds Replit’s first party cloud infrastructure so users can build, scale, and succeed entirely on Replit. They manage databases, application storage, app publishing and hosting, development/production environment splitting, custom domains, and more. By having a set of first party services that integrate seamlessly, you will power one of Replit’s key product differentiators. You will: Work closely with designers and product managers, to quickly iterate on Replit Cloud to continually grow and improve the product. Drive full-stack feature development from conception to deployment, taking ownership of key product initiatives. Contribute to architectural decisions that shape the future of our product. Ship product and build infrastructure as a true full stack builder using: TypeScript, React, CSS, Postgres, Go, and Terraform. Examples of what you could do: Leverage our unique cloud infrastructure to build differentiated full product experiences, helping non-technical or semi-technical users remove roadblocks to success. Leverage AI agents to proactively optimize or suggest app improvements on latency, reliability, SEO, and more. Be part of engineering leadership, steering teams towards the highest impact work and supporting initiatives across the company. Required skills and experience: Bachelor’s degree in Computer Science or related field, OR equivalent real-world experience in engineering roles. Comfortable building with our tech stack: TypeScript, React, Go Preferred Qualifications Experience building user facing platform as a service products. Experience with AI/agentic systems. Previous e

Most PMs write specs and wait for feedback. You'll be deploying AI agents with real customers across APAC, then turning what you learn into product direction that actually matters. The Company Sendbird is on a mission to build the AI workforce of tomorrow. For over a decade, we built the infrastructure behind conversations—chat, voice, video, messaging APIs—and became the #1 CPaaS platform for in-app communications. 4,000+ brands trust us. 7 billion messages flow through our platform every month. 300 million monthly active users. We powered conversations for DoorDash, Match Group, Noom, Yahoo Sports, Rakuten, and thousands of others. We were good at what we did. Really good. We also saw it early: AI would fundamentally reshape how businesses talk to customers. The infrastructure we'd spent a decade building would become commoditized. The value would move up the stack—into intelligence, into experience, into outcomes. We had a choice: protect what we built, or reinvent ourselves. We chose reinvention. In December 2024, we made the full strategic pivot to AI-first customer experience. By February 2025, we'd launched our AI agent for enterprise CX—built on a decade of conversation data, now with intelligence on top. And in November 2025, we rebranded to delight.ai. The name says it all. AI's real promise isn't efficiency or cost savings. It's giving customers back something they lost—the feeling of being truly understood and cared for. Not satisfied. Delighted. The Product Delight.ai is the AI concierge for customer experience. Most AI agents forget you the moment the conversation ends. Ours doesn't. Delight.ai builds memory over time, learns preferences, and connects context across every channel—chat, SMS, email, voice, WhatsApp—without losing the thread. We're building AI that makes customers feel understood, seen, and remembered. Why Forward Deployed Product Manager Enterprise AI isn't won in the roadmap, it's won in the field. Businesses across APAC are trying to f

For over 20 years, Smartsheet has empowered teams to manage work seamlessly and scale solutions smarter. Now, in our most ambitious chapter yet, we are uniting human teams with AI agents. By orchestrating the work agents do best, automating manual tasks and uncovering insights at scale, we create the space for people to focus on what truly matters: judgment, creativity, and big thinking. That is magic at work, and it’s what we show up for every day. You independently lead the most complex AI deployments Smartsheet undertakes. You own the full engagement lifecycle from technical discovery through production deployment through solutions org handoff. You architect multi-agent solutions, design client-personalized MCP resource packs, and build the Deployment Kits that transform how 200+ solutions consultants and partners operate. You mentor junior FDEs, drive the intelligence loop, and present field findings at weekly Applied AI strategy sessions. You are building a function, not filling a role. What You Will Do Lead complex, multi-system AI deployments end-to-end scope, architect, build, validate, and manage the customer relationship throughout. Own the AI workshop program for your pod, customize modules per customer, lead technical sessions, translate outputs into production requirements, evolve content from field learning. Architect multi-agent solutions selecting the right coordination pattern for each customer’s workflow characteristics and compliance requirements. Design client-specific and industry-specific MCP resource packs that serve personalized intelligence from the server so every connected AI surface gets smarter for that customer automatically. Own Deployment Kit quality for your pod. If a kit is not documented well enough for a solutions consultant with no engineering background to follow, it isn’t done. Lead Solutions Enablement Sprints: transfer AI deployment patterns to solutions consultants and partners with training materials and certification crite