AI Engineer

About the Job: The AI Engineer supports the day-to-day design, operation, and continuous improvement of enterprise AI platforms, applications, and agentic workflows. This role combines hands-on engineering, applied solution delivery, and cross-functional collaboration to help establish secure, scalable, governed, and practical AI capabilities that support real business processes. This role applies engineering judgment across a broad and evolving set of activities, including platform configuration, integrations, governed data access, retrieval pipelines, evaluation, deployment, monitoring, and continuous improvement. The AI Engineer works closely with Cybersecurity, Infrastructure, Data, Operations, and business stakeholders to translate emerging AI capabilities into secure and compliant business outcomes. Key Responsibilities: Design, operate, and continuously improve enterprise AI platforms, services, integrations, and governance capabilities that enable secure, scalable, and reliable AI adoption Administer and support AI platforms, agent services, and enterprise controls, including identity, access management, observability, provisioning, lifecycle management, and governance workflows Implement and maintain security controls, auditing capabilities, data protection measures, and compliance guardrails in partnership with Cybersecurity, Data, Infrastructure teams Design and develop secure integrations that enable AI applications and agents to interact with approved enterprise systems, tools, and governed data assets Scope, build, deploy, and support AI applications, copilots, and agentic workflows that address business needs while operating within established technical and governance guardrails Develop and maintain retrieval-based and tool-enabled AI solutions using approved knowledge sources and governed data assets to support accurate, traceable, and reproducible outcomes Establish and execute evaluation, monitoring, testing, and continuous improvement practices that ensure AI solutions remain effective, reliable, and fit for purpose Maintain production engineering practices , including code quality, deployment pipelines, instrumentation, version control, operational readiness, and platform reliability Drive enablement and scale by providing design guidance, reusable patterns, reference implementations, documentation, and practical support for internal builders and stakeholders Comply with FMI's attendance policies Qualifications: Basic Qualifications: Bachelor's Degree and 2+ years of experience designing, building, and operating production software platforms or cloud solutions on Azure and/or AWS, including at least 2 years developing and supporting LLM-powered applications in production environments Strong software engineering and cloud platform expertise , including Python, APIs, CI/CD, containers, infrastructure as code (Terraform), version control, observability, and secure deployment practices Hands-on experience designing enterprise AI solutions , including prompt engineering, structured outputs, tool calling, context engineering, evaluation frameworks, agentic workflows, and production AI application delivery Demonstrated experience implementing retrieval-augmented generation (RAG) and enterprise knowledge solutions , including content ingestion, embeddings, vector search, re-ranking, grounding strategies, and evaluation of AI-generated outputs Experience integrating AI platforms with enterprise systems and governed data , including authentication and authorization patterns, MCP or equivalent tool integration frameworks, APIs, OAuth, and secure access controls Strong knowledge of enterprise AI, cloud, and security platforms , including Azure AI Foundry, Azure OpenAI Service and/or AWS Bedrock, Entra ID, managed identities, IAM, Conditional Access, and related governance and compliance controls Proven ability to work effectively with business, data, security, and technology stakeholders , translating requirements into practical solutions while operating within established governance, risk, compliance, and operational guardrails Preferred Qualifications: Experience developing or operating AI, data, or software platforms in regulated industries such as healthcare, biotechnology, genomics, pharmaceuticals, or financial services Familiarity with regulatory and compliance frameworks including HIPAA, GxP, 21 CFR Part 11, validated systems, audit trails, and emerging AI regulations Experience with AWS Bedrock, Azure AI Foundry, Anthropic Claude, Bedrock AgentCore, Claude Code, or similar enterprise AI technologies Familiarity with AI governance, evaluation, and risk management frameworks such as NIST AI RMF Experience with fine-tuning, distillation, open-weight models, or cost- and latency-optimized AI deployments Contributions to open-source AI tooling, agent frameworks, MCP servers, or evaluation frameworks Relevant Microsoft or AWS certifications Demonstrated commitment to responsible AI, security and compliance Understanding of HIPAA and the importance of patient data privacy Commitment to reflect FMI’s values: Integrity, Courage, and Passion The expected salary range for this position based on the primary location of Boston, MA is $111,040 - $138,800 per year. The salary range is commensurate with Foundation Medicine’s compensation practice and considers factors including, but not limited to, education, training, experience, external market conditions, criticality of role, and internal equity. A discretionary annual bonus may be available based on individual and Company performance. This position also qualifies for Foundation Medicine's benefits. #LI-Hybrid