Senior AI Solutions Engineer

Location: Hartford, CT – Need locals

Nature of Job: 5 days in the office

Duration: 6+ months

Interview Mode: Video

What's the Job?

Lead forward-deployed engagements from discovery through production deployment for agentic AI solutions in the insurance industry. Design, build, and scale GenAI and Agentic AI solutions using Google Cloud technologies such as Vertex AI, Gemini, BigQuery, Agent Builder, Cloud Run, and related services. Translate underwriting, claims, pricing, distribution, and servicing challenges into production-ready AI products that drive measurable business outcomes. Apply strong LLM application design practices including prompt engineering, agent orchestration, RAG architectures, evaluation frameworks, and AI governance. Prototype rapidly and iterate quickly—moving from concept to working demonstrations within days—while contributing reusable accelerators and best practices across engagements.

What's Needed?

5–10 years of experience in solution engineering, AI engineering, forward-deployed engineering, consulting, or enterprise application development, preferably in client-facing roles. Hands-on experience building GenAI and Agentic AI solutions on Google Cloud (Vertex AI, Gemini, BigQuery, Agent Builder, Cloud Run, and related services). Strong understanding of LLM application design, prompt engineering, agent orchestration, RAG architectures, evaluation frameworks, and AI governance. Experience designing and integrating enterprise applications, APIs, data platforms, and workflow solutions. Insurance domain expertise in Property & Casualty, Life, Reinsurance, or Specialty Insurance operations, including familiarity with underwriting, claims, pricing, actuarial, policy administration, customer servicing, or distribution/broker operations.

What's in it for me?

Opportunity to deliver agentic AI solutions that create measurable impact across underwriting, claims, and customer-facing workflows. Work in a forward-deployed environment where you can collaborate closely with business and technology stakeholders to drive outcomes. Build reusable accelerators and best practices that strengthen delivery across multiple engagements. Use modern Google Cloud AI capabilities to design, prototype, and deploy production-ready solutions. Join a team that values experimentation, rapid iteration, and clear communication with executives and technical teams.