Develop and test AI/ML solutions for multiple use cases spanning underwriting, claims, operations, and/or corporate functions.
Collaborate with Data Science Practitioners, LOB IT leads, EA, Data, and AI architects to develop solutions and integrate into operational processes and systems supporting various functions.
Build and maintain scalable Agentic AI systems.
Build full stack AI Agents with latest Agentic AI/UI frameworks & standards.
Build reusable components, APIs, SDKs, Agents, MCP tools for the enterprise.
Apply context engineering and prompt tuning techniques.
Develop advanced RAG systems, with hybrid search and metadata filtering.
Instrument AI observability using OpenTelemetry (OTel) tooling.
Build scalable, fault-tolerant solutions on AWS and/or GCP in a multi cloud ecosystem.

Requirements

A bachelor’s or master’s degree in computer science, Software Engineering, Data Science, or a closely related discipline.
3+ years of experience in Machine Learning, Software Engineering or related field, with at least 1+ years focused on AI or ML
1+ years of experience in GenAI/Agentic AI, RAG, semantic search, embedding models and LLMs.
Strong programming skills in Python.
Experience with AI Agent frameworks such as ADK, LangChain, LangGraph, and/or CrewAI.
Hands-on experience in GenAI tools and services on Google cloud platform (Vertex AI/Gemini Ent).
Experience with Agile development methodologies, including SAFe.
Experience with NodeJS, JavaScript, Typescript, React is a plus.
Understanding of data structures, NoSQL and RDBMS is a plus.
Candidate must be authorized to work in the US without company sponsorship.

Benefits

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

Machine LearningAIGenAIAgentic AIRAGsemantic searchembedding modelsLLMsPythonAgile