Summary role description:

 

Hiring for a Solution Architect (Agentic AI) for an InsurTech platform provider.

 

Company description:

 

Our client is a VC-funded InsurTech platform company, providing software platforms for Life Insurance and Health Insurance companies across the globe. Leveraging their domain expertise, regulatory knowledge and technology experience, they architect innovative products and disrupt the Insurance value chain from Customer Acquisition to Engagement. Their products serve customers across the APAC region.

 

Role details:

 

Title / Designation: Solution Architect Location: Pune, India Work Mode: Work-from-Office

 

Role & responsibilities:

 

Architect and evolve the Agentic AI frameworks powering autonomous insurance workflows (underwriting, claims, servicing). Design multi-agent systems capable of reasoning, decision-making, and adaptive task execution. Define the AI/ML architecture roadmap for intelligent document processing (IDP), fraud/waste/abuse detection (FWA), and end-to-end insurance automation. Build and scale cloud-native AI platforms across the full ML lifecycle — from experimentation to production deployment. Collaborate with product teams, data scientists, and engineering to ensure architecture aligns with customer needs and business goals. Represent the architecture team in customer discussions, pre-sales, solutioning, and product workshops. Drive innovation by exploring emerging technologies in LLMs, prompt chaining, agent orchestration, and GenAI tooling.

 

Candidate requirements:

 

10+ years of experience in software/system architecture, with the recent 5+ years into designing and deploying AI/ML systems, including LLM-driven platforms. Hands-on experience building Agentic AI systems — not just prompt engineering or chatbots, but agents that act, integrate with tools/APIs, and execute multi-step workflows autonomously. Experience with use cases in life or health insurance is highly preferred — such as claims management, policy onboarding, or risk assessment. Strong experience in cloud-native architecture (AWS preferred), microservices, containerization (Docker, Kubernetes), and MLOps. Familiarity with multi-agent frameworks, LLMOps pipelines, and fine-tuning techniques like LoRA, PEFT. Ability to lead technical discussions across cross-functional teams and customers.

 

Selection process:

 

Interview with Senior Solution Architect Interview with CTO HR Discussion

 

Recruiter Details

 

Name: Rajesh Ravi Email ID: [email protected]