Senior Forward Deployed Engineer

Senior Forward Deployed Engineer

Remote role, open to U.S. based candidates.

Essential Functions and Responsibilities

• Owns a build stream end to end within a pod: problem shaping with the Principal, implementation, production operation, and instrumentation of the outcome the business said it would measure.
• Designs, builds, and operates production Generative AI agents, workflows, and applications — including request orchestration, tool execution, state management, and interaction with enterprise systems.
• Develops full-stack software in Python and React, shipping both the service and the interface a business user touches.
• Owns deployment and operation on AWS, with infrastructure as code in Terraform and CI/CD in GitHub Actions, including environments, secrets, and repeatable promotion to production.
• Implements evaluation, observability, and human-in-the-loop controls for AI systems: provenance on material outputs, confirmation on consequential claims actions, and evidence that a workflow is ready to move up the autonomy ladder.
• Implements authentication, authorization, logging, monitoring, and error handling to meet enterprise security, auditability, PHI, and reliability requirements.
• Integrates AI services with enterprise and legacy systems — including APIs, data platforms, and event streams — using approved, non-invasive patterns and versioned contracts.
• Stewards a shared capability as assigned (context, documents, agents, or assurance), with authority to block a duplicate build in another pod.
• Embeds with vendor delivery teams for co-development when the stream requires it: shared repositories in Sedgwick accounts, shared definition of done, not acceptance testing after a demo.
• Sits with examiners, nurse reviewers, or operations staff; watches the work; and turns that into scoped services, workflows, and UI changes.
• Provides technical guidance and mentoring to Junior AI Engineers, promoting engineering standards, code quality, and operational excellence.
• Troubleshoots and leads root cause analysis and performance optimization for latency, throughput, cost, correctness, and reliability of production AI services.
• Evaluates and recommends improvements to architecture, platform capabilities, and engineering process for the stream and the shared substrate.

Additional Functions and Responsibilities

• Performs other duties as assigned.
• Travel as required, including 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

Six (6) + years of software engineering experience, with at least three (3) years shipping production Generative AI agents, workflows, or applications — including evaluation, failure handling, and a human review loop — or an equivalent combination of education and experience.

Hands-on experience building and operating production workloads on AWS required. Cloud certification without production ownership is not sufficient.

Hands-on experience with Python, React, GitHub Actions, and Terraform required, including ownership of CI/CD and infrastructure rather than editing templates.

Experience embedding with business users or a vendor delivery team to co-develop, rather than receiving a completed specification, preferred.

Experience in insurance, claims, healthcare, or another heavily regulated operational domain preferred.

Skills & Knowledge

• Strong full-stack engineering skills in Python and React, with solid working knowledge of SQL, REST APIs, and service design
• Hands-on AWS: has built, deployed, and operated production services, including networking, identity, and operational concerns sufficient for a regulated environment
• Hands-on GitHub Actions and Terraform: owns pipelines and infrastructure as code, including review, drift, and recovery
• Production command of Generative AI agents, workflows, and applications — tool use, orchestration, evaluation, and human-in-the-loop patterns — sufficient to ship and run, not only prototype
• Ability to implement services in alignment with enterprise architecture, governance, PHI handling, and compliance requirements
• Ability to sit with examiners or operations staff and leave with scoped work; comfortable as the only engineer in that room
• Ability to work collaboratively in a fast-paced Transformation Office, including pairing with vendor engineers when required
• Strong mentoring, collaboration, and technical communication skills
• 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

Sedgwick is an Equal Opportunity Employer and a Drug-Free Workplace.

If you're excited about this role but your experience doesn't align perfectly with every qualification in the job description, consider applying for it anyway! Sedgwick is building a diverse, equitable, and inclusive workplace and recognizes that each person possesses a unique combination of skills, knowledge, and experience. You may be just the right candidate for this or other roles.