Jobs and Careers

Senior AI Engineer, Legal - USA Remote

USA - Remote, United States, United StatesRemotefull_timeVerifiedPosted 6 Jul 2026

💰 $200,000/yr($185,000/yr – $200,000/yr)

About the role

Bring more to life.

At Danaher, our work saves lives. And each of us plays a part. Fueled by our culture of continuous improvement, we turn ideas into impact – innovating at the speed of life. 

Our 60,000+ associates work across the globe at more than 15 unique businesses within life sciences, diagnostics, and biotechnology.  

Are you ready to accelerate your potential and make a real difference? At Danaher, you can build an incredible career at a leading science and technology company, where we’re committed to hiring and developing from within. You’ll thrive in a culture of belonging where you and your unique viewpoint matter. 

Learn about the Danaher Business System which makes everything possible.

The Senior Legal Engineer is responsible for designing, building, and deploying AI-powered solutions that transform legal and compliance workflows across Danaher's corporate and platform functions and operating companies. This role sits at the intersection of software engineering, data science, and legal operations — applying deep technical expertise in large language models (LLMs), agentic AI, and modern AI infrastructure to solve high-impact legal problems at enterprise scale.

In this role, you will have the opportunity to:

Partner with legal stakeholders to translate workflows into technical solutions — Conduct discovery with attorneys and compliance professionals across Danaher to understand their workflows, identify automation opportunities, and deliver solutions that legal teams trust and adopt.
Architect and build AI-powered legal applications. Design end-to-end solutions for contract review, legal research, regulatory analysis, and compliance workflows using LLMs, retrieval-augmented generation (RAG), and agentic AI frameworks. Develop and optimize document processing pipelines. Build scalable ingestion, parsing, chunking, embedding, and indexing systems for legal content (contracts, playbooks, regulatory filings) to power intelligent search and analysis.
Ship production-grade AI features. Write clean, well-tested code (Python and/or TypeScript) to deliver production applications using LLM APIs, orchestration frameworks (e.g., LangChain, LlamaIndex), and CI/CD pipelines — from prototype through deployment and monitoring. Design evaluation and quality framework. Build automated evaluation pipelines, test sets, and quality metrics specific to legal AI outputs, ensuring accuracy, consistency, and defensibility of AI-generated work product.
Embed governance and security by design — Implement data security controls, access management, audit logging, PII redaction, and data residency compliance appropriate for applications handling privileged and confidential legal content. Apply product thinking to legal AI solutions — Understand user needs through discovery and feedback, translate them into clear product and technical requirements, and help prioritize features that drive adoption and measurable business value.
Technical leadership and mentorship - Lead, educate and mentor legal team members in developing no-code AI solutions. Serve as the technical bridge between legal and engineering. Communicate clearly across disciplines, deliver demos and training to legal users, and channel user insights back into product development and roadmap priorities. Partner closely with IT, Data & AI teams to design, build, and deliver scalable AI solutions aligned with enterprise architecture and governance standards.

The essential requirements of the job include:

Bachelor's degree in Computer Science, Data Science, Engineering, or a related technical field (Master's or advanced degree is a plus). 5+ years of professional experience in software engineering, data science, or machine learning engineering, with a track record of shipping production applications.
Production experience with large language models (LLMs), including prompt engineering, fine-tuning, RAG architecture, agent/tool-use development, and evaluation frameworks. Strong programming proficiency in Python, with experience in AI/ML libraries and frameworks (e.g., LangChain, LlamaIndex, Hugging Face, or equivalent orchestration tools); proficiency in an additional lang