Principal AI Engineer

Principal AI Engineer Remote role open to all U.S. states. ESSENTIAL FUNCTIONS AND RESPONSIBILITIES • Owns the technical outcome of a value-stream pod from problem shaping through production operation, including whether work contributes to shared capability or is incomplete. • Partners directly with business transformation leadership, examiners, nurse reviewers, and operations - sitting with users, shaping ambiguous problems, and refusing work that would wire new capability onto a process known to be broken. • Architects and personally builds production Generative AI agents, workflows, and applications, contributing code in Python and React rather than reviewing from a distance. • Sets and enforces engineering standards for the pod: API-first and contract-first delivery, AWS and Terraform as the path to production, GitHub Actions as the CI/CD bar, evaluation and observability as release gates, and human confirmation on consequential claims actions. • Accountable for whether the pod lands on shared substrate (context, documents, agents, assurance) or forks it; exercises stewardship and design-council authority to block duplicate builds. • Defines interface terms with vendor delivery teams when the stream is co-developed: shared repositories in Sedgwick accounts, Sedgwick-owned contracts, shared definition of done. • Establishes evaluation, provenance, and autonomy-ladder evidence for AI workflows - what may auto-complete, what must ask then do, and what is not ready - with the business owning thresholds. • Leads technical solution design and architectural review for the stream; escalates conflicts with enterprise standards (identity, model egress, PHI, portability) rather than absorbing them quietly. • Represents the pod on the AI Engineering design council; operates independently and is expected to converge with peer Principals without requiring SVP arbitration for ordinary technical disagreement. • Provides technical guidance and mentoring to Senior and Junior AI Engineers; raises the pod's bar on code quality, operational excellence, and forward-deployed practice. • Leads complex troubleshooting, root cause analysis, and performance optimization for business-critical AI services and platforms. • Evaluates and recommends whether a capability should be built in-house, co-developed with a vendor, or not built - with a named owner and a removal path when a compromise is accepted. ADDITIONAL FUNCTIONS AND RESPONSIBILITIES• • Performs other duties as assigned. • Travel as required, including regular on-site work with claims or Managed Care operations and with vendor delivery teams. QUALIFICATIONS Education & Licensing Bachelor's degree in Computer Science, Engineering, or a related quantitative discipline from an accredited college or university required. Master's degree preferred. Experience Ten (10)+ or more years of software engineering experience, including at least four (4) years owning production Generative AI or applied-AI systems in the field - agents, workflows, or applications, including evaluation, failure handling, and a human review loop - or an equivalent combination of education and experience.Hands-on production experience on AWS, and hands-on Python, React, GitHub Actions, and Terraform, at a level sufficient to set the bar for a pod, not only meet it. Cloud certification or architecture-only experience without recent production code is not sufficient.Experience leading technical delivery for a value stream or equivalent without people-management authority.Experience in insurance, claims, healthcare, or another heavily regulated operational domain preferred. Skills & Knowledge • Expert full-stack engineering skills in Python and React, with strong SQL, APIs, and service design; still writes production code • Deep, hands-on AWS, Terraform, and GitHub Actions - including identity, networking, environments, and operational recovery - sufficient to set standards and review others' work • Production command of Generative AI agents, workflows, and applications, including tool use, orchestration, evaluation, provenance, and human-in-the-loop patterns • Ability to walk into a design session with examiners or operations leaders and leave with a shaped problem, scoped build, and explicit non-goals • Ability to keep a pod on shared substrate and to stop a duplicate build without escalating every conflict • Ability to set interface terms with vendors and internal platform teams while remaining a peer IC, not a manager of either • Strong mentoring, collaboration, and technical communication skills with the ability to influence transformation leadership, architecture, security, and engineering peers • Experience with machine learning, model fine-tuning, and/or graph databases (e.g. Neo4j) preferred • Experience with PydanticAI (or equivalent agent framework), agent observability, and AI Ops / LLMOps a plus • Ability to meet or exceed Performance Competencies WORK ENVIRONMENT When applicable and appropriate, consideration will be given to reasonable accommodation. Mental: Clear and conceptual thinking ability; excellent judgment, troubleshooting, problem solving, analysis, and discretion; ability to handle work-related stress; ability to handle multiple priorities simultaneously; and ability to meet deadlines Physical: Computer keyboarding, travel as required Auditory/Visual: Hearing, vision and talking