AI Agent Developer Jobs
AI Agent Developer jobs are open across technology, finance, healthcare, and enterprise software, from junior to staff and principal engineer, with specializations in LLM orchestration, autonomous workflow design, and multi-agent systems. See the openings below and apply to the ones that match your experience.
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Job Description:
Overview:
We don’t simply hire employees. We invest in them. When you work at Chatham, we empower you — offering professional development opportunities to help you grow in your career, no matter if you've been here for five months or 15 years. Chatham has worked hard to create a distinct work environment that values people, teamwork, integrity, and client service. You will have immediate opportunities to partner with talented subject matter experts, work on complex projects, and contribute to the value Chatham delivers every day.
We are seeking an AI Agent Developer to design, build, and deploy AI agents that transform how teams at Chatham work. This is a hands-on engineering role for someone who wants to apply modern AI to real business problems and see the impact firsthand. You will report to one of our Software Engineering Directors to maintain alignment with our organizational AI objectives.
In each role, you will embed with a partner team as a forward-deployed engineer. You will review past work, shadow team members on live tasks, and map where time is spent and why. From there, you will identify and prioritize the highest-value opportunities, then build, evaluate, and release agents that triage requests, research and draft answers, investigate issues across systems and data, and prepare work for review. The team’s experts stay in the loop throughout, and people review agent output before it reaches a client or a production system.
Once a team’s agents are running reliably, you will hand them over to the people who own the work and bring the same approach to the next team. Over time, you will partner with teams across the firm, from engineering and operations to client service and Marketing, wherever repetitive work can be improved through agentic means. You will work closely with Chatham’s AI evaluation and platform teams and help set the standards that other teams adopt.
This is a new role at Chatham and an opportunity to help define how the firm builds and scales agentic capabilities. The ideal candidate is a pragmatic engineer who enjoys learning new domains from the people who do the work, collaborates easily with technical and non-technical colleagues, and measures success by the problems solved for users.
In this role you will:
Discovery & Partnership
- Embed in a partner team and learn how it works. Review past work, shadow live tasks, and map the steps that the team repeats.
- Find and rank the tasks where agents can save the most time or improve quality and agree on priorities with the team’s leaders.
- Work closely with the team’s experts. They supply the domain knowledge and test cases, and they review agent output.
Agent Development
- Design, build, and deploy cloud-native AI agents that do repetitive work from documented processes, with a person in the loop where judgment is necessary.
- Build agents that triage and route incoming requests, research questions and draft answers, and investigate issues across systems, logs, and data.
- Build agents that prepare work for people to review, such as draft responses, reports, and code changes as merge requests.
- Turn each team’s playbooks and procedures into agent instructions and tools and keep them current as processes change.
Evaluation & Quality
- Create evaluation sets from real past work. Measure each agent’s accuracy before release and whenever models or techniques change and monitor the results in production.
- Partner with our AI evaluation team, and adopt its tools, techniques, and processes as they mature.
- Follow Chatham’s standards for security, data handling, and the responsible use of AI.
Reuse & Handover
- Document each agent’s purpose, tools, and limits so that other teams can adopt and extend it.
- Build reusable tools and patterns that make each new team’s agents faster to deliver.
Your Impact:
For each partner team
- Agents do a growing share of the team’s routine work correctly, and people review the output.
- The team spends less time on repetitive tasks and more time on work that needs judgment.
- Requests that wait in a queue today get faster and more consistent answers.
- Each agent meets its accuracy targets before release and keeps them in production.
Across Chatham
- Each agent has documentation and tests, and other teams reuse its tools and patterns.
- Each engagement ends with a clean handover to the people who own the work.
Contributors to your success:
- 3+ years of professional software engineering experience.
- Strong proficiency in Python or C#, with experience in APIs, services, or automation.
- Hands-on experience with applications built on large language models (LLMs), including prompt and context design, tool use, and agent workflows.
- Experience with evaluation of AI output: test sets, accuracy measures, and regression checks for systems that do not always return the same answer.
- Solid SQL skills, and comfort with logs and telemetry to find the root cause of a problem.
- Experience with Git, code review, and CI/CD.
- Curiosity and patience to learn complex business domains from the people who do the work.
- Ability to turn a business process into clear steps that an agent can follow, and to judge where a person must stay in the loop.
- Clear written and verbal communication with technical and non-technical colleagues.
- Experience with tools and integrations built on the Model Context Protocol (MCP).
- Experience with platforms or frameworks for AI agents, such as Microsoft Foundry or the Claude Agent SDK.
- Daily use of AI coding tools such as Claude Code, Codex or GitHub Copilot.
- Experience in a forward-deployed, solutions engineering, or internal tools role, or a background in operations, technical support, or site reliability engineering.
- Experience with Azure.
About Chatham Financial:
Chatham Financial is the leading independent capital markets advisor, delivering an integrated blend of expert advice and powerful technology to help you reduce risk and seize opportunity. With decades of capital markets strategy, execution, monitoring, and performance expertise, we serve as an unwavering advocate for your best interests and your innovation partner. Our technology platform unifies data across assets, debt, and derivatives, giving you unmatched agility, transparency, and insight.
It’s clear ahead.
Our commitment is to carry that light forward in every partnership, every solution, and every market we serve.
We help guide the way—giving clients the insight and momentum to move forward with confidence, no matter what lies ahead.
Job Description:
Overview:
We don’t simply hire employees. We invest in them. When you work at Chatham, we empower you — offering professional development opportunities to help you grow in your career, no matter if you've been here for five months or 15 years. Chatham has worked hard to create a distinct work environment that values people, teamwork, integrity, and client service. You will have immediate opportunities to partner with talented subject matter experts, work on complex projects, and contribute to the value Chatham delivers every day.
We are seeking an AI Agent Developer to design, build, and deploy AI agents that transform how teams at Chatham work. This is a hands-on engineering role for someone who wants to apply modern AI to real business problems and see the impact firsthand. You will report to one of our Software Engineering Directors to maintain alignment with our organizational AI objectives.
In each role, you will embed with a partner team as a forward-deployed engineer. You will review past work, shadow team members on live tasks, and map where time is spent and why. From there, you will identify and prioritize the highest-value opportunities, then build, evaluate, and release agents that triage requests, research and draft answers, investigate issues across systems and data, and prepare work for review. The team’s experts stay in the loop throughout, and people review agent output before it reaches a client or a production system.
Once a team’s agents are running reliably, you will hand them over to the people who own the work and bring the same approach to the next team. Over time, you will partner with teams across the firm, from engineering and operations to client service and Marketing, wherever repetitive work can be improved through agentic means. You will work closely with Chatham’s AI evaluation and platform teams and help set the standards that other teams adopt.
This is a new role at Chatham and an opportunity to help define how the firm builds and scales agentic capabilities. The ideal candidate is a pragmatic engineer who enjoys learning new domains from the people who do the work, collaborates easily with technical and non-technical colleagues, and measures success by the problems solved for users.
In this role you will:
Discovery & Partnership
- Embed in a partner team and learn how it works. Review past work, shadow live tasks, and map the steps that the team repeats.
- Find and rank the tasks where agents can save the most time or improve quality and agree on priorities with the team’s leaders.
- Work closely with the team’s experts. They supply the domain knowledge and test cases, and they review agent output.
Agent Development
- Design, build, and deploy cloud-native AI agents that do repetitive work from documented processes, with a person in the loop where judgment is necessary.
- Build agents that triage and route incoming requests, research questions and draft answers, and investigate issues across systems, logs, and data.
- Build agents that prepare work for people to review, such as draft responses, reports, and code changes as merge requests.
- Turn each team’s playbooks and procedures into agent instructions and tools and keep them current as processes change.
Evaluation & Quality
- Create evaluation sets from real past work. Measure each agent’s accuracy before release and whenever models or techniques change and monitor the results in production.
- Partner with our AI evaluation team, and adopt its tools, techniques, and processes as they mature.
- Follow Chatham’s standards for security, data handling, and the responsible use of AI.
Reuse & Handover
- Document each agent’s purpose, tools, and limits so that other teams can adopt and extend it.
- Build reusable tools and patterns that make each new team’s agents faster to deliver.
Your Impact:
For each partner team
- Agents do a growing share of the team’s routine work correctly, and people review the output.
- The team spends less time on repetitive tasks and more time on work that needs judgment.
- Requests that wait in a queue today get faster and more consistent answers.
- Each agent meets its accuracy targets before release and keeps them in production.
Across Chatham
- Each agent has documentation and tests, and other teams reuse its tools and patterns.
- Each engagement ends with a clean handover to the people who own the work.
Contributors to your success:
- 3+ years of professional software engineering experience.
- Strong proficiency in Python or C#, with experience in APIs, services, or automation.
- Hands-on experience with applications built on large language models (LLMs), including prompt and context design, tool use, and agent workflows.
- Experience with evaluation of AI output: test sets, accuracy measures, and regression checks for systems that do not always return the same answer.
- Solid SQL skills, and comfort with logs and telemetry to find the root cause of a problem.
- Experience with Git, code review, and CI/CD.
- Curiosity and patience to learn complex business domains from the people who do the work.
- Ability to turn a business process into clear steps that an agent can follow, and to judge where a person must stay in the loop.
- Clear written and verbal communication with technical and non-technical colleagues.
- Experience with tools and integrations built on the Model Context Protocol (MCP).
- Experience with platforms or frameworks for AI agents, such as Microsoft Foundry or the Claude Agent SDK.
- Daily use of AI coding tools such as Claude Code, Codex or GitHub Copilot.
- Experience in a forward-deployed, solutions engineering, or internal tools role, or a background in operations, technical support, or site reliability engineering.
- Experience with Azure.
About Chatham Financial:
Chatham Financial is the leading independent capital markets advisor, delivering an integrated blend of expert advice and powerful technology to help you reduce risk and seize opportunity. With decades of capital markets strategy, execution, monitoring, and performance expertise, we serve as an unwavering advocate for your best interests and your innovation partner. Our technology platform unifies data across assets, debt, and derivatives, giving you unmatched agility, transparency, and insight.
It’s clear ahead.
Our commitment is to carry that light forward in every partnership, every solution, and every market we serve.
We help guide the way—giving clients the insight and momentum to move forward with confidence, no matter what lies ahead.
See All 307+ AI Agent Developer Jobs
Find roles that match your experience and apply in just a few clicks.
Find AI Agent Developer JobsAI Agent Developer Job Market
Who's Hiring
- Booz Allen Hamilton20
- JPMorganChase11
- Johns Hopkins University Applied Physics Laboratory9
- University of San Diego6
- Penn State University4
Top Industries Hiring
- Technology & Software10
- Education8
- Banking & Financial Services6
- Healthcare & Medical Services5
- Insurance3
What Employers Look For
The qualifications that appear most often in AI agent developer jobs.
- Proficiency in Python and at least one agent framework such as LangChain, AutoGen, or CrewAI
- Experience designing and deploying LLM-powered autonomous or multi-agent systems in production
- Strong understanding of prompt engineering, context management, and tool-use patterns
- Familiarity with retrieval-augmented generation, vector databases, and embedding pipelines
- Ability to build evaluation frameworks and monitor agent reliability and failure modes
- Bachelor's degree in computer science, software engineering, or a related technical field
Tips for Your AI Agent Developer Job Search
Show agents shipping, not just built
Hiring managers want proof your agents ran in production, not just in a notebook. For each project on your resume, state the framework you used, what the agent was tasked with, and the outcome it reliably delivered at scale.
Tailor your stack to each listing
AI agent roles vary sharply by toolchain. One company ships with LangChain and OpenAI, another with AutoGen and local models. Read each job description carefully and mirror the specific frameworks and APIs they name before you apply.
Apply early to roles that fit
Migrate Mate lists ai agent developer openings from across the United States in one place, so you can find roles that match and apply directly to each listing.
Build a public evaluation suite
Interviewers increasingly ask how you measure agent reliability. Publish a small eval harness on a public code repository that tests an agent you built. It demonstrates rigor most candidates skip and gives your interviewer something concrete to discuss.
Prep for adversarial agent scenarios in interviews
Expect questions about what happens when your agent loops, hallucinates a tool call, or exceeds a context window mid-task. Walk through how you detect failure, surface it to the user, and recover gracefully without breaking the broader workflow.
Negotiate scope alongside compensation
AI agent teams are still small at most companies, so the role's boundaries are often undefined. During offer conversations, clarify which models and infrastructure you'll own, what your deployment authority is, and whether you'll set evaluation standards yourself.
AI Agent Developer Jobs: Frequently Asked Questions
Which companies are hiring the most ai agent developers?
The most active employers for ai agent developers right now are Booz Allen Hamilton, JPMorganChase, and Johns Hopkins University Applied Physics Laboratory, and the most openings are in Virginia, California, and Texas, based on current listings on Migrate Mate as of November 2026. Demand is concentrated in companies building enterprise automation, AI-native software products, and internal productivity tooling.
How many ai agent developer jobs are remote?
About 55% of ai agent developer openings are fully remote or hybrid as of November 2026, reflecting the broader trend in software engineering roles. Sub-areas with the highest remote share include agent framework development, LLM integration, and backend orchestration work, since those tasks require minimal on-site coordination.
How do you become an ai agent developer?
Start by building strong Python fundamentals and practical experience with large language model APIs. Learn at least one agent orchestration framework by shipping a project where an agent uses tools, manages memory, and handles failures. Study evaluation methods so you can measure reliability. Then contribute to open-source agent projects or document your builds publicly to establish a credible portfolio before applying.
How do you get hired as an ai agent developer with little or no experience?
Build and publish a working agent that solves a real, narrow task, such as a research assistant that queries external tools and summarizes results. Document your design decisions, failure modes you encountered, and how you resolved them. Hiring managers in this space weigh demonstrated curiosity and practical output heavily because the field is new enough that most candidates lack years of formal experience.
What does the ai agent developer interview process look like?
Most processes include a recruiter screen, a technical phone interview covering LLM fundamentals and system design, and a take-home or live coding exercise where you build or extend a small agent. Final rounds typically include a system design session focused on multi-agent coordination or failure handling, plus conversations with engineering leads about production architecture and evaluation standards.
Where can I find and apply to ai agent developer jobs?
You can find and apply to ai agent developer jobs on Migrate Mate, which lists current openings from across the United States. Search the listings to find roles that match your experience level and tech stack, then apply directly to each one that fits.
See All 307+ AI Agent Developer Jobs
Find roles that match your experience and apply in just a few clicks.
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