Senior Principal Software and AI Engineer

BeOne Medicines

. Architect, build, and deploy AI and agentic applications for protocol generation and clinical trial execution .

Posted 10/16/2026full-timeRemote • United StatesSenior💰 $137,400 - $182,400 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in architecting and deploying AI and agentic applications, with a strong focus on multi-agent orchestration, LLMOps, and compliance with GxP and data privacy standards. Proven ability to lead cross-functional teams, mentor engineers, and manage product development from concept to production.

Highest-signal resume keywords

AI/ML Engineering ExperienceDeep Backend Expertise in PythonExperience Shipping Production-Grade AI ApplicationsStrong Knowledge of LLMOpsExperience with Clinical Protocol Development

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

AI/ML EngineeringSoftware EngineeringBackend DevelopmentMulti-Agent Application ArchitectureModel ValidationKnowledge Architecture DesignCI/CD ExperienceData Store ManagementTool IntegrationOrchestration

Soft Skills

MentoringCollaborationLeadershipCommunicationProject Management

Tools & Technologies

PostgreSQLElasticsearchNeo4jAWSAzureGCPAI Coding ToolsMCPCI/CD ToolsObservability Tools

Industry Keywords

GxPData PrivacyClinical Trial OperationsICH M11CDISC StandardsUSDMComputer System ValidationEmerging Regulatory GuidanceAI in Drug DevelopmentHuman-in-the-Loop Controls

Tech Stack

Tools & technologies

AWSAzureCloudElasticSearchGoogle Cloud PlatformNeo4jPostgresPythonSDLC.NET

About the role

Key responsibilities & impact

Architect, build, and deploy AI and agentic applications for protocol generation and clinical trial execution
Accelerate workflows from study design through operational delivery
Partner with clinicians, medical writers, statisticians, data scientists, clinical operations, and product teams
Define scalable and reliable architecture for multi-agent orchestration, model and tool integration, and the full LLMOps lifecycle
Establish best practices for AI-native development, evaluation, testing, observability, and continuous performance monitoring within a validated SDLC
Assess frontier and open-weight models, agent frameworks, and tooling
Make build, buy, and model sourcing decisions
Uphold GxP, data privacy, security, and responsible AI standards
Build traceability, auditability, and human oversight into systems
Own product development and technical direction from concept through production
Lead project execution, 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

What you’ll need

Bachelor's degree with 7+ years of experience, Master's degree with 5+ years of experience, or PhD with 3+ years of experience
Software and AI/ML engineering experience
Experience as a tech lead or principal engineer owning large-scale AI products end to end
Experience shipping production-grade AI and agentic applications
Strong software engineering background
Deep backend expertise in Python and/or .NET
Experience architecting enterprise applications across frontend, APIs, databases, and deployment
Hands-on experience with PostgreSQL, Elasticsearch, and Neo4j or similar relational, search, and graph data stores
Experience architecting and shipping multi-agent applications to production
Experience with agent harness design, context engineering, orchestration, tool integration including MCP, and human-in-the-loop controls
Experience selecting and applying frontier and open-weight models
Experience with structured outputs, guardrails, and model validation
Experience with fine-tuning or post-training is a plus
Ability to design and manage enterprise knowledge architecture, ontology design, knowledge graphs, and retrieval
Ability to build multi-layered evaluations and production monitoring
Fluency with AI coding tools and practices
Rigorous testing, code review, and CI/CD experience
Strong knowledge of LLMOps, secure cloud deployment using AWS, Azure, or GCP, and observability
Experience with clinical protocol development, study design, or clinical trial operations
Familiarity with ICH M11 structured protocols, CDISC standards, or USDM is a strong plus
Working knowledge of GxP, computer system validation, and emerging regulatory guidance on AI in drug development
Proven ability to act as tech lead, own product direction and delivery, and mentor senior engineers
Ability to partner with clinicians, medical writers, statisticians, and clinical operations
Commitment to data privacy, security, and responsible AI
Willingness to travel 10%

Benefits

Comp & perks

Annual bonus plan eligibility for non-commercial roles
Incentive compensation plan eligibility for commercial roles
Discretionary equity awards
Employee Stock Purchase Plan
Medical insurance
Dental insurance
Vision insurance
401(k)
FSA/HSA
Life Insurance
Paid Time Off
Wellness