Principal Forward Deployed Engineer

Sedgwick•Telecommuter FL, FL

2d•Remote

About The Position

The Principal Forward Deployed Engineer owns the technical outcome of a value-stream pod from problem shaping through production operation. The role works directly with business transformation leadership and operations users to shape ambiguous problems, build production Generative AI agents and applications, and determine whether work contributes to shared capabilities or should not proceed. This is a hands-on individual-contributor role, writing production code in Python and React while leading technical delivery without people-management authority. The position sets engineering standards for the pod, including API-first and contract-first delivery, AWS and Terraform for production, GitHub Actions for CI/CD, evaluation and observability as release gates, and human confirmation for consequential claims actions. It stewards shared technical capabilities, establishes evaluation and provenance evidence for AI workflows, conducts architectural reviews, and resolves or escalates conflicts with enterprise standards. The role also works with vendor delivery teams to define shared repositories, contracts, and delivery expectations; mentors AI engineers; and leads troubleshooting, root-cause analysis, and performance optimization. The role is remote and open to U.S.-based candidates, with travel as required, including regular onsite work with claims or Managed Care operations and vendor teams.

Requirements

Bachelor’s degree in Computer Science, Engineering, or a related quantitative discipline from an accredited college or university.
Ten or more years of software engineering experience.
At least four years owning production Generative AI or applied-AI systems in the field, including agents, workflows, or applications with evaluation, failure handling, and a human review loop; an equivalent combination of education and experience is also accepted.
Hands-on production experience with AWS, Python, React, GitHub Actions, and Terraform, sufficient to set engineering standards for a pod.
Recent production coding experience; 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.
Expert full-stack engineering skills in Python and React, with strong SQL, API, and service-design skills, and willingness to continue writing production code.
Deep, hands-on AWS, Terraform, and GitHub Actions experience, including identity, networking, environments, and operational recovery.
Production command of Generative AI agents, workflows, and applications, including tool use, orchestration, evaluation, provenance, and human-in-the-loop patterns.
Ability to shape problems, scope builds, and define explicit non-goals with examiners or operations leaders.
Ability to keep a pod on shared substrate and stop duplicate builds without escalating every conflict.
Ability to set interface terms with vendors and internal platform teams while remaining a peer individual contributor.
Strong mentoring, collaboration, and technical communication skills, with the ability to influence transformation leadership, architecture, security, and engineering peers.
Ability to meet or exceed Performance Competencies.
Ability to handle work-related stress, multiple priorities, and deadlines; clear and conceptual thinking, judgment, troubleshooting, problem solving, analysis, and discretion.
Ability to keyboard, travel as required, and meet hearing, vision, and talking requirements.

Nice To Haves

Master’s degree.
Experience in insurance, claims, healthcare, or another heavily regulated operational domain.
Experience with machine learning, model fine-tuning, and/or graph databases such as Neo4j.
Experience with PydanticAI or an equivalent agent framework, agent observability, and AI Ops/LLMOps.

Responsibilities

Own the technical outcome of a value-stream pod from problem shaping through production operation, including determining whether work contributes to shared capability or is incomplete.
Partner with business transformation leadership, examiners, nurse reviewers, and operations users to shape ambiguous problems and avoid building on processes known to be broken.
Architect and personally build production Generative AI agents, workflows, and applications, contributing code in Python and React.
Set and enforce engineering standards for API-first and contract-first delivery, AWS and Terraform, GitHub Actions, evaluation, observability, and human confirmation for consequential claims actions.
Ensure the pod uses shared capabilities rather than creating duplicate builds, and exercise design-council authority to block duplication.
Define interface terms with vendor delivery teams, including shared repositories in Sedgwick accounts, Sedgwick-owned contracts, and a shared definition of done.
Establish evaluation, provenance, and autonomy-ladder evidence for AI workflows, with the business owning thresholds.
Lead technical solution design and architectural review, escalating conflicts with enterprise standards such as identity, model egress, PHI, and portability.
Represent the pod on the AI Engineering design council and converge with peer Principals on technical decisions.
Provide technical guidance and mentoring to Senior and Junior AI Engineers and improve code quality, operational excellence, and forward-deployed practice.
Lead complex troubleshooting, root-cause analysis, and performance optimization for business-critical AI services and platforms.
Evaluate and recommend whether capabilities should be built in-house, co-developed with a vendor, or not built, with a named owner and removal path for accepted compromises.
Perform other duties as assigned.
Travel as required, including regular onsite work with claims or Managed Care operations and vendor delivery teams.