Accountabilities

You will act as a bridge between clients, commercial teams, and technical delivery specialists, translating insurance operational challenges into practical agentic AI solutions that demonstrate clear business value.

Discover client needs: Participate in client meetings and workshops alongside Sales and Client Experience teams to understand operational goals, challenges, and existing workflows.

Identify automation opportunities: Evaluate processes such as submission intake, data enrichment, classification, quoting, bind checking, policy checking, and certificate management to identify where agentic AI can deliver the greatest impact.

Map operational workflows: Document current-state processes, including activities, handoffs, systems, documents, and stakeholders, and develop future-state journey maps.

Design and build prototypes: Rapidly develop functional agentic AI prototypes using real AI tools, synthetic data, and simulated systems that reflect clients' operational environments.

Define human-AI collaboration: Design agent-plus-expert workflows, clarifying which activities agents can perform autonomously, which require human review, and when escalation is necessary.

Iterate and improve solutions: Incorporate client feedback and refine prototypes to demonstrate credible, practical, and measurable improvements.

Demonstrate business value: Present prototypes and future-state workflows to operational stakeholders and executives, explaining their potential impact in accessible business terms.

Support commercial development: Partner with Sales to develop business cases based on cost savings, reduced processing times, improved accuracy, and other relevant performance indicators.

Shape client commitments: Contribute to proposals, proof-of-concept (POC) scopes, and success criteria to ensure proposed solutions are realistic and achievable.

Coordinate technical handoffs: Transfer prototypes, journey maps, and technical requirements to forward-deployed delivery teams for POC and production development.

Maintain AI governance standards: Follow approved AI models, tools, and governance practices, using synthetic data instead of real client information during prototyping.

Build reusable resources: Develop and maintain a library of prototypes, synthetic datasets, and journey-map templates while sharing market insights with product teams.

Requirements

The ideal candidate combines deep insurance industry knowledge, hands-on experience building AI-powered solutions, and strong client-facing consulting and commercial skills.

At least 8 years of experience in insurance operations, distribution, or Insurtech, with direct exposure to agency, brokerage, Managing General Agent (MGA), or insurance carrier workflows.

At least 2 years of experience designing, building, or managing AI and automation solutions in roles such as Product Manager, Solutions Engineer, Sales Engineer, or Consultant.

Demonstrated experience taking at least some AI or automation solutions into production.

Proven ability to rapidly build functional agentic AI prototypes using tools and platforms such as Claude, ChatGPT, OpenAI API, Microsoft Copilot Studio, n8n, LangGraph, or comparable frameworks and low-code platforms.

Experience developing synthetic datasets and simulated systems to support realistic AI prototyping, rather than relying exclusively on presentations or click-through demonstrations.

Hands-on understanding of large language model (LLM) systems, including agent workflow design, Retrieval-Augmented Generation (RAG), prompt engineering, schema design, and evaluation.

Strong discovery, listening, and facilitation skills, with the ability to understand complex operational processes and translate them into current-state and future-state journey maps.

Experience collaborating with Sales, Client Experience, or account management teams in pre-sales, solution design, or client advisory environments.

Ability to develop compelling business cases for automation, demonstrating measurable improvements in cost efficiency, processing time, and accuracy.

How Jobgether works

We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.

We appreciate your interest and wish you the best!

Why Apply Through Jobgether?

Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.

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