Principal, AI Engineer; Remote
Morristown, Morris County, New Jersey, 07960, USA
Listed on 2026-09-01
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Software Development
AI Engineer (Applied/Software), Software Architect, Machine Learning/ ML Engineer, AI Reliability/ Performance Engineer
Principal Ai Engineer (Genai & Agentic Ai)
Crum & Forster is seeking a Principal AI Engineer (GenAI & Agentic AI) to lead the AI solution architecture, and delivery of next-generation AI solutions that transform insurance operations. This role will drive the adoption of Generative AI and Agentic AI across underwriting, claims, policy servicing, and corporate functions by building enterprise-grade applications, intelligent automation, and AI-powered assistants.
As a senior technical leader, you will partner with business and technology stakeholders to identify high-value opportunities, establish scalable AI architecture patterns, and deliver secure, responsible, and measurable AI solutions.
This is a unique opportunity to help build C&F's next generation AI capabilities from the ground up, influencing enterprise AI strategy, defining engineering standards, and delivering high-impact solutions in a largely greenfield environment.
This role is fully remote within the United States.
What you will do:
AI solution design and technical authority
- Lead the architecture, design, and implementation of enterprise-scale Generative AI and agentic AI solutions including the target-state solution design for generative and agentic AI - foundation model integration, retrieval-augmented generation, tool use, orchestration frameworks, and multi-agent patterns.
- Define the reusable AI capability and pattern library that federated teams build on, so that capability is built once and inherited rather than rebuilt.
- Leads AI solution design reviews across central and federated builds and provide technical sign-off within the AI readiness gates.
- Set technical standards for evaluation, groundedness, guardrails, observability, security and cost engineering, and hold builds to them.
- Evaluate AI platforms and tooling and recommend direction in alignment with Enterprise Architecture standards.
Hands-on build and delivery
- Personally design, build and deliver the foundational shared AI capabilities - platform, runtime, retrieval primitives, agent frameworks, and the evaluation harness.
- Lead the technical delivery of prioritized flagship initiatives that establish the pattern for everything that follows.
- Build AI-powered assistants, copilots, workflow automation, and knowledge retrieval systems that improve business outcomes and employee productivity.
- Leverage AWS Bedrock, Bedrock Agent Core, MCP and related technologies to build scalable, secure, and maintainable AI applications.
Standards, quality, and responsible AI
- Establish and enforce engineering practices for AI evaluation, model risk, observability, auditability, and responsible AI, in partnership with the AI Risk and Reliability Engineering Lead.
- Ensure every AI solution is instrumented for groundedness, quality, drift, and cost from the first commit rather than retrofitted before go-live.
Enablement and technical mentorship
- Provide technical leadership and mentorship to AI engineers within the central team and to engineers building AI within federated development domains.
- Lead the technical Community of Practice: shared libraries, office hours, code and design reviews, and internal enablement on agentic engineering.
- Partner with external accelerators to absorb expertise into the ADLC practice, mentor engineers and provide technical leadership across AI platform and application development efforts
- Stay current on emerging AI technologies and recommend approaches that create business value.
What you will bring to C&F:
- Bachelor's degree or equivalent in computer science, Engineering, Data Science, or a related field.
- 10+ years of experience in software engineering, solution architecture, platform engineering, or AI/ML development.
- 4+ years of hands-on experience designing and delivering Generative AI, AI-Native, or LLM-based solutions in production environments.
- Demonstrated experience building agentic AI systems in production - orchestration, tool calling, retrieval frameworks, reasoning workflows, and autonomous task execution.
- Track record of defining technical standards or solution patterns adopted by engineering teams beyond the candidate's own team.
- Experience leading design review or…
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