AI / Agent Engineer

Responsibilities

• Build and evolve MCP servers, tools, and skills for use with multiple large language models.
• Design and refine graph-RAG pipelines that transform documents into agent-friendly facts, entities, and relationships.
• Implement multi-tier retrieval across source documents, vector RAG, and dense graphs, including temporal replay.
• Partner with QA on evaluation-driven improvements to answer quality and factual grounding.
• Write production-grade, well-tested code and participate in code reviews.
• Collaborate with product, data, and QA teams in an agile/sprint model.
• Document designs, prompts, and tool interfaces for maintainability and handover.
• Monitor deployed agents and models, troubleshoot issues, and improve performance.
• Stay current with LLM and agent tooling.

Requirements

• Bachelor’s degree in Computer Science, Engineering, or equivalent practical experience.
• At least 5 years of software engineering experience, including at least 2 years in AI/ML or LLM-based applications.
• Strong Python skills and hands-on experience developing LLM applications and agentic patterns.
• Direct experience building MCP servers, tools, and skills.
• Experience with RAG, graph-RAG systems, vector databases, and embeddings.
• Familiarity with graph data stores such as Neo4j and Postgres/Supabase-based graph implementations.
• Experience working with multiple LLM providers, such as Claude and Gemini.
• Solid software engineering fundamentals, including version control and testing.
• Strong problem-solving, communication, collaboration, and independent-working skills.
• Prior consulting experience.
• Life Sciences industry experience and connections are preferred.

Benefits

• Equal Opportunity Employer committed to diversity, equity, and inclusion.
• Accommodations are available upon request throughout the recruitment process.