AI/ML / Generative AI Developer Agentic AI

Relevance Lab; Los Angeles (CA); On-site; USD 150,000 - 230,000; Full time

Job summary

Relevance Lab in Los Angeles is seeking an experienced AI/ML/GenAI Developer to build and deploy enterprise-grade AI solutions using AWS Bedrock and AgentCore. You will help architect an Agent Factory platform and GenAI-powered agents for insurance processes.

The role requires hands-on Python development, experience with Bedrock, and data pipelines to support AI applications. US-based candidates in the LA area preferred and alignment with Pacific Time.

Qualifications

• 6–8 years of experience in software engineering, AI/ML development, or related roles.
• Hands-on Python development with AWS cloud services.
• Experience building GenAI applications and LLM-powered workflows.
• Experience with Amazon Bedrock and Bedrock AgentCore.
• Knowledge of API integration and enterprise data sources.

Responsibilities

• Design, develop, and deploy GenAI agents and autonomous AI workflows using AWS Bedrock.
• Contribute to an Agent Factory framework for building and managing AI agents.
• Develop AI agents to support Insurance business processes and automation.
• Build scalable data ingestion, transformation, and ETL/ELT pipelines for AI apps.
• Implement retrieval-augmented generation, vector databases, and prompt engineering.

Skills

Python

AWS Cloud

Tools

Amazon Bedrock

Bedrock AgentCore

Amazon Quick

Data Pipelines

LLM integration

REST APIs

CI/CD

Docker

Terraform

MLOps/LLMOps

Job description

Job Description: AI/ML / Generative AI Developer Agentic AI

Experience: 6 8 Years

Location: United States Los Angeles, CA

Time Zone: Must be available to work Pacific Time (PST/PDT)

Domain: Insurance

Technology Stack: AWS Bedrock, Amazon Bedrock AgentCore, Amazon Quick, Python, GenAI, Agentic AI, Data Engineering

Role Overview

We are seeking an experienced AI/ML / Generative AI Developer with strong hands-on expertise in building and deploying enterprise‑grade AI solutions using AWS technologies. The ideal candidate will play a key role in developing an Agent Factory platform and GenAI‑powered intelligent agents to automate business processes and enhance operational efficiency within the Insurance domain. The role requires expertise in Agentic AI development, AWS Bedrock, Amazon Bedrock AgentCore, Amazon Quick, and building scalable data pipelines to support AI‑driven applications.

Key Responsibilities

• Design, develop, and deploy GenAI agents and autonomous AI workflows using AWS Bedrock and Amazon Bedrock AgentCore.
• Contribute to the development of an Agent Factory framework for building, deploying, orchestrating, and managing reusable AI agents.
• Develop intelligent agents to support Insurance business processes, workflow automation, and decision support.
• Build and maintain scalable data ingestion, transformation, and ETL/ELT pipelines to support AI/ML applications.
• Develop and integrate LLM‑based applications using Retrieval‑Augmented Generation (RAG), prompt engineering, vector databases, and agent orchestration frameworks.
• Leverage Amazon Quick to enable AI‑powered enterprise workflows and intelligent automation.
• Integrate AI agents with enterprise applications, APIs, databases, and external tools.
• Implement agent monitoring, evaluation, security, and governance to ensure reliable production deployments.
• Collaborate with data engineering, cloud architecture, and business teams to deliver scalable GenAI solutions.
• Optimize AI models, agent performance, and cloud infrastructure for scalability, reliability, and cost efficiency.

Required Skills (Must‑Have)

• 6 8 years of experience in software engineering, AI/ML development, or related technical roles.
• Strong hands‑on development experience with Python and AWS cloud services.
• Practical experience building GenAI applications, LLM‑powered workflows, and AI agents.
• Experience with Amazon Bedrock and Amazon Bedrock AgentCore.
• Knowledge or hands‑on experience with Amazon Quick and AI‑powered enterprise automation.
• Experience designing and developing data pipelines using AWS Glue, Lambda, S3, or similar technologies.
• Strong understanding of RAG architectures, embeddings, vector databases, prompt engineering, and LLM integration.
• Experience integrating REST APIs, tools, and enterprise data sources into AI applications.
• Understanding of secure, scalable, production‑ready AI application development.

Good‑to‑Have Skills

• Experience with LangChain, LangGraph, CrewAI, or AWS Strands Agents.
• Familiarity with Model Context Protocol (MCP), multi‑agent orchestration, and agent‑to‑agent communication.
• Experience with AWS Step Functions, SageMaker, DynamoDB, and OpenSearch.
• Knowledge of CI/CD, Docker, Terraform, and MLOps/LLMOps practices.
• Experience working in the Insurance domain, including claims processing, underwriting, policy administration, or customer servicing.
• Exposure to AI governance, model evaluation, observability, and responsible AI practices.

Preferred Candidate Profile

A hands‑on AI/ML or GenAI Developer who has successfully designed and deployed production‑grade GenAI solutions, possesses strong AWS expertise, and can independently build intelligent agents and supporting data pipelines. The candidate must be US‑based, comfortable working Pacific Time hours, and ideally located in the Los Angeles area.