Agent Post-Training, Connectors Research

Details

About the team

The Agent Post-Training team creates the frontier agents OpenAI ships to the world. The team trains the models behind 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. The team defines next-generation agent abilities, builds training signal, and runs experiments spanning coding, tool use, computer use, multi-agent coordination, long-horizon execution, factuality, instruction following, calibrated reasoning, and taste.

About the role

As a member of Agent Post-Training, Connectors, you will teach models how to interface with professional software using code. You will help train agents to use code, APIs, tools, and structured integrations to operate across applications like Slack, Google Workspace, GitHub, Notion, Linear, Salesforce, and other core systems of work. You will enable models to take useful actions across a user's digital context: finding information, updating systems, coordinating work, generating artifacts, and completing multi-step workflows through the tools teams already use. You will work with researchers, engineers, product teams, infrastructure teams, and safety/alignment partners to decide what should go into major model runs, measure outcomes, and ship improvements into products used by real people.

Responsibilities

• Design and run experiments that improve agentic model behavior for complex software and plugins.
• Own end-to-end improvements to the post-training stack, including reinforcement learning (RL), data pipelines, graders, reward signals, evaluations, diagnostics, and model-behavior analysis.
• Build evals and environments that expose model failures, then turn failures into training data, product fixes, or new research directions.
• Partner with Codex and ChatGPT product teams to translate product signal into model improvements.
• Work on early-training and alignment interventions, including data mixtures, objectives, synthetic data, and evaluation loops that shape downstream agent behavior.
• Help decide which integrations, capabilities, and fixes are ready for inclusion in major model runs.
• Improve the machinery for large-scale training and launch: experiment velocity, reliability, observability, reproducibility, cost, latency, and production readiness.
• Take on cross-functional projects touching model training, product infrastructure, and the production agent harness (for example, multi-agent systems or training against production-like environments).
• Debug hard failures in shipped or near-shipped models and turn qualitative behavior into hypotheses, experiments, and fixes.

Requirements

• Strong technical fundamentals in machine learning, software engineering, systems, statistics, or a related field, with an ability to learn quickly across areas you have not worked in before.
• Hands-on experience with LLMs, reinforcement learning (RL), RLHF/RLAIF, post-training, evaluations, graders, synthetic data, model training, coding agents, tool-using agents, or production ML systems.
• Experience designing experiments: formulating hypotheses, building pipelines, running models, analyzing results, and iterating on interventions.
• Comfortable working across research, product, infrastructure, data, evals, and safety boundaries and communicating clearly with each group.
• Product-focused mindset: care about model behavior and real user impact (reliability, honesty, tastefulness, usefulness).
• Willingness to build load-bearing systems and processes when needed.

Benefits

• Base pay range listed: $295K – $445K (base may vary by location, experience, and other factors).
• Equity and performance-related bonuses for eligible employees.
• Medical, dental, and vision insurance with employer contributions to Health Savings Accounts.
• Pre-tax accounts: Health FSA, Dependent Care FSA, and commuter accounts.
• 401(k) retirement plan with employer match.
• Paid parental leave, medical and caregiver leave, flexible PTO, paid company holidays, and sick/safe time as required by law.
• Mental health and wellness support; employer-paid basic life and disability coverage.
• Annual learning and development stipend.
• Daily meals in offices and meal delivery credits as eligible.
• Relocation support for eligible employees.
• Additional taxable fringe benefits (charitable donation matching, wellness stipends) and more details provided during hiring.

About OpenAI

OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. The company emphasizes safety, diverse perspectives, and provides reasonable accommodations for applicants with disabilities. Background checks are administered in accordance with applicable law.