Gen AI Architect

Job Details:

Experience: 10+ Years

Role Overview:

We are seeking a Tech Lead with deep expertise in architecture, system design, and Generative AI to lead high-impact projects across strategic insurance clients. The ideal candidate will combine technical depth with business acumen to translate client problems into scalable AI-driven solutions. Experience in the insurance domain is highly preferred.

Key Responsibilities:

• Lead the architecture and technical solutioning for GenAI-powered use cases in the insurance industry.
• Work closely with business teams to ideate, assess, and create use cases that demonstrate tangible value.
• Design end-to-end systems that incorporate GenAI components, APIs, and cloud infrastructure.
• Own and drive technical delivery, ensuring scalability, performance, and alignment with client goals.
• Collaborate with engineers, product managers, and QA to deliver production-grade solutions.
• Serve as the technical face to the client, supporting solution discussions and managing stakeholder expectations.
• Evaluate and select the right set of GenAI tools and platforms (e.g., OpenAI, LangChain, RAG pipelines, etc.).
• Ensure data privacy, compliance, and security standards are upheld in every solution.

Required Skills & Experience:

• 10+ years in software development/architecture with a strong track record in system design and enterprise delivery.
• Proven experience in designing AI/ML or GenAI solutions, preferably using tools like OpenAI, Azure OpenAI, LangChain, etc.
• Strong understanding of cloud infrastructure (AWS/Azure/GCP) and integration best practices.
• Experience working with insurance workflows like underwriting, claims, policy administration, or financial operations.
• Ability to create clear technical documentation, architecture diagrams, and engineering playbooks.
• Hands-on development experience in Python, Node.js, or similar languages is a plus.
• Strong stakeholder management and communication skills.

Preferred Qualifications:

• Exposure to GenAI use cases in insurance (e.g., submission intake, risk summarization, broker email parsing, etc.)
• Experience working in Agile teams and fast-paced innovation environments.
• Familiarity with vector databases, retrieval-augmented generation (RAG), and MLOps pipelines.
• Prior experience leading cross-functional engineering teams.