Principal AI Engineer

We're building a world of health around every individual , shaping a more connected, convenient and compassionate health experience.

As a Principal AI Engineer, you will set the technical direction for designing, building, and operating enterprise-grade GenAI and agentic AI systems in a regulated healthcare environment.

What You Will Do

• Architect and deliver production-grade GenAI and agentic AI solutions, including RAG, vector search, model integration, tool orchestration, guardrails, and evaluation across AWS and/or GCP.
• Build scalable, cloud-native AI systems using serverless/event-driven architectures, APIs, CI/CD, infrastructure-as-code, and modern software engineering practices.
• Own the production AI lifecycle, from experimentation and deployment through monitoring, observability, performance, cost optimization, and continuous improvement.
• Establish secure and responsible AI practices that address privacy, security, governance, auditability, model risk, and appropriate human oversight in a regulated environment.
• Define AI architecture, standards, and engineering best practices for areas such as agent orchestration, RAG, tool/MCP integrations, evaluation, and enterprise AI adoption.
• Partner across product, engineering, data, security, privacy, legal, compliance, and business teams to translate strategic needs into scalable AI solutions and influence technical direction.
• Provide hands-on technical leadership through design reviews, mentorship, architecture guidance, build-vs-buy decisions, and clear technical documentation.

Required Qualifications

• 10+ years of software engineering experience, with 5+ years in solution architecture or system design.
• 5+ years building large-scale microservices and APIs (Node.js, TypeScript, Java, or Python).
• 5+ years of hands-on AWS and/or GCP experience (serverless, event-driven, CI/CD, AI/ML).
• Hands-on experience with AWS Bedrock (models, agents, knowledge bases, guardrails, tuning, evaluation) or GCP Vertex AI (Model Garden, Agent Builder, Vector Search, Pipelines, Tuning), or equivalent.
• Production experience with agentic AI frameworks, RAG architectures, and vector databases.
• Strong Python skills for AI/ML engineering.
• Demonstrated experience delivering AI/ML systems in regulated environments with security, privacy, and audit requirements.
• Track record of influencing technical direction across multiple teams without direct authority.

Preferred Qualifications

• Healthcare, life sciences, or other regulated-industry experience, including HIPAA and PHI handling.
• Experience with Vertex AI Generative AI Studio, vector search orchestration, and agent capabilities.
• Experience with LLM evaluation tooling and observability platforms (e.g., LangSmith, Arize, Langfuse, Ragas, or cloud-native equivalents).
• Experience with MCP servers and tool integration, agent-to-agent patterns, and agent memory design.
• Experience with infrastructure-as-code (Terraform, CDK), containers, and Kubernetes.
• Experience with fine-tuning techniques (LoRA/PEFT, distillation) and open-weight models.
• Familiarity with AI governance frameworks (NIST AI RMF, ISO 42001) and model risk management.
• Agile/SAFe experience in large enterprises.
• Cloud certifications (AWS, GCP, or Azure).
• Publications, patents, or open-source contributions in AI/ML.

Education

• Bachelor’s degree in Computer Science, Engineering, or a related field, or equivalent experience (High School diploma + 4 years of relevant experience).

Pay Range

The typical pay range for this role is: $144,200.00 - $288,400.00