Agentic AI Sr. Engineer
About The Position
Design, build, and operate agentic and LLM-powered systems for biologics scientists, taking ownership from concept to production. Build custom agentic skills and tools that encode scientific expertise for domain-specific work. Connect agents to internal data, models, and services using approved integration platforms, adhering to data and security standards. Develop and deploy LLM and agentic applications end-to-end, including interfaces and supporting engineering for authentication, logging, evaluation, and error handling. Construct digital pipelines to transfer data between models, lab platforms, and scientists. Collaborate with protein scientists, computational biologists, platform engineers, and teams like BIX, EAI, and R&D IT, prioritizing shared platforms over isolated development. Document work in GitHub and Confluence, ensuring maintainability, extensibility, and compliance with safety, quality, and FAIR data practices.
Requirements
- MS degree in Computer Science, Software Engineering, Computational Biology, Data Science, or a related quantitative field, or equivalent demonstrated ability.
- 3–10 years of relevant software engineering experience.
- Proven, hands-on experience building agentic AI systems and deploying them to production.
- Solid Python and/or TypeScript programming skills.
- Hands-on experience in software development best practices: clean code, version control, testing.
- Practical experience building with LLMs and agent frameworks, including tool and function calling, retrieval, and orchestration of multi-step workflows.
- Fluency with modern agentic developer tools such as Claude Code, Copilot, or similar, used daily.
- Clear written and verbal communication, with the ability to explain technical choices to scientists who are not engineers.
- Working knowledge of Unix, SQL databases, REST APIs, and cloud computing (AWS).
Nice To Haves
- Experience with tool-integration layers that connect agents to enterprise data, models, and services.
- Experience with AI frameworks such as Pydantic-AI, LangChain, or similar.
- Experience building production retrieval-augmented generation (RAG) pipelines and working with vector databases.
- Experience in at least one compiled programming language (e.g., C, Java, Go, or Rust).
- Experience with the evaluation and guardrails that make LLM applications trustworthy, and cloud deployment practice: containers, Kubernetes, CI/CD, and platforms such as Domino.
- Familiarity with laboratory automation, high-throughput platforms, or scientific data.
- Awareness of responsible-AI and compliance considerations in a regulated environment.
- Curiosity about biology and drug discovery.
Responsibilities
- Design, build, and operate agentic and LLM-powered systems.
- Build custom agentic skills and tools.
- Connect agents to internal data, models, and services.
- Build and deploy LLM and agentic applications end to end.
- Build the digital pipelines that move data between models, lab platforms, and scientists.
- Partner with scientists and engineers.
- Document work in GitHub and Confluence.
- Meet relevant safety, quality, and compliance standards, including FAIR data practices.
Benefits
- Qualified retirement programs
- Paid time off (i.e., vacation, holiday, and leaves)
- Health coverage
- Dental coverage
- Vision coverage
- Eligibility for various incentives
- Opportunity to receive short-term incentive bonuses
- Equity-based awards for salaried roles
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What This Job Offers
Job Type
Full-time
Career Level
Senior
