Sr. Principal Software and AI Engineer

BeOne Medicines USA, Inc. is seeking a senior technical leader to build and deploy AI-powered applications for drug development, especially protocol generation and clinical trial execution. The role sets engineering architecture and standards, ensures compliant and reliable production systems, and leads and mentors cross-functional engineering work.

Responsibilities:

• Build AI and Agentic Applications: Architect, build, and deploy AI and agentic powered applications that accelerate protocol generation and clinical trial execution, from study design through operational delivery
• Collaborate Broadly: Partner with clinicians, medical writers, statisticians, data scientists, clinical operations, and product teams to embed AI into regulated clinical development workflows
• Shape Architecture: Define scalable, reliable platform architecture for multi-agent orchestration, model and tool integration, and the full LLMOps lifecycle
• Set Standards: Establish best practices for AI-native development, evaluation, testing, observability, and continuous performance monitoring within a validated SDLC
• Drive Innovation: Assess frontier and open-weight models, agent frameworks, and tooling, and make sound build, buy, and model sourcing decisions
• Ensure Compliance: Uphold GxP, data privacy, security, and responsible AI standards, with traceability, auditability, and human oversight built into every system
• Act as tech lead with full ownership of product development, accountable for technical direction, delivery, and quality from concept through production
• Lead project execution, setting priorities, scope, and timelines for the AI engineering team
• Mentor AI and software engineers through design and code reviews, reference implementations, and hands-on guidance
• Lead cross-functional technical workstreams with clinical, medical writing, biostatistics, and clinical operations partners

Requirements:

• Bachelors with 7+ years, Masters with 5+ years or PhD with 3+ years
• Software and AI/ML engineering experience, including experience as a tech lead or principal engineer owning large-scale AI products end to end
• Proven success shipping production-grade AI and agentic applications that deliver measurable scientific or business impact
• A strong software engineer first. Deep backend expertise in Python (preferred) and/or .NET, with a track record of architecting and building enterprise applications end to end across frontend, APIs, databases, and deployment. Hands-on experience with relational, search, and graph data stores such as PostgreSQL, Elasticsearch, and Neo4j. Sound judgment in system design, data modeling, and production operations
• Deep, hands-on experience architecting and shipping multi-agent applications to production, with strong command of agent harness design, context engineering, orchestration, tool integration (including MCP), and human-in-the-loop controls
• Strong judgment in selecting and applying frontier and open-weight models, using structured outputs, guardrails, and validation to ensure stable, robust model behavior
• Proven ability to design and manage enterprise knowledge architecture, including ontology design, knowledge graphs, and retrieval, to make domain knowledge structured, governed, and usable by AI systems
• Proven ability to build multi-layered evaluation, from expert benchmarks and rule-based checks to human review and model-based grading, backed by production monitoring
• Fluency with AI coding tools and practices, applied within a disciplined SDLC with rigorous testing, code review, and CI/CD
• Strong knowledge of LLMOps, secure cloud deployment (AWS, Azure, or GCP), and observability
• Experience with clinical protocol development, study design, or clinical trial operations
• Working knowledge of GxP, computer system validation, and emerging regulatory guidance on AI in drug development
• Proven ability to act as tech lead, owning product direction and delivery while mentoring senior engineers
• Strong partnership with clinicians, medical writers, statisticians, and clinical operations, translating complex AI concepts for research, regulatory, and executive audiences
• Deep commitment to data privacy, security, and responsible AI in development and deployment
• Experience in the pharmaceutical or life sciences industry is strongly preferred
• ideally in a regulated environment
• Python (preferred)
• Experience with fine-tuning or post-training is a plus
• Familiarity with ICH M11 structured protocols, CDISC standards, or USDM is a strong plus