Lead Agent Engineer

About the role

The Lead Agent Engineer will set the technical ceiling on the platform's core capabilities, including translation accuracy, dependency-map correctness, hallucination control, and multi-agent orchestration. This role involves driving the prompt-and-eval iteration cycle in partnership with the RAG & Eval Engineer, owning the agent layer of the platform, and establishing foundational patterns for the rest of the team.

Responsibilities

• Set the technical ceiling for the platform’s core capabilities: translation accuracy, dependency-map correctness, hallucination control.
• Drive translation and dependency-mapping accuracy across an unfamiliar legacy paradigm — call graphs, data references, semantic equivalence checks.
• Take on capability bets that don’t show up on most roadmaps yet — agent work at the frontier of code understanding.
• Drive the prompt-and-eval iteration cycle in partnership with the RAG & Eval Engineer.
• Write production agent code daily; subagents and multi-agent workflows are your normal way of working.
• Establish foundations the rest of the team builds against — agent architecture, eval loop, prompt-and-tool patterns, multi-agent topology.

Requirements

• Bachelor’s degree in Computer Science, Engineering, or a related field, plus 5 years of professional software engineering experience; equivalent experience may substitute for the degree requirement.
• Has shipped at least one production agent (real users, real failure modes) and can describe in detail what broke and how it was fixed.
• Ability to work in a fast-paced, collaborative environment.
• Working fluency across the modern agent stack: tool use, MCP, evals, RAG, streaming, multi-agent coordination.
• Strong TypeScript or Python.
• Subagents and multi-agent workflows are a normal way of working.
• Comfort with measurement, regression detection, and prompt-and-eval iteration.
• Able to operate without a roadmap — defines the next problem worth solving and goes.
• Heavy native use of AI tooling: agents in parallel, model as collaborator.
• Ability to operate in a remote work environment.
• Prior architectural ownership of an agent platform; track record of establishing eval and prompt patterns for a team.

Qualifications

• Strong background in compilers, program analysis, or static/dynamic code understanding.
• Open-source contributions to agent frameworks, MCP servers, or eval harnesses.
• Legacy-language or legacy-system exposure (rare, but a plus).
• Public technical writing or conference talks on production agent work.
• Healthcare IT or legacy modernization domain experience.

Skills

• Native use of AI tooling: agents in parallel, model as collaborator.

Benefits

LTS offers a comprehensive benefits package for you and your family, including access to cutting-edge tools and technologies, and opportunities for career growth and development.

Pay

LTS shares salary ranges to promote transparency. Final compensation may vary based on experience, skills, location, and role requirements.

Schedule

Details on the schedule will be shared during the interview process.