Software Engineer/Lead Software Engineer

State Farm•Dunwoody, GA

7h•Hybrid

About The Position

Enterprise Technology’s Customer Communications team is seeking a Software Engineer or a Lead Software Engineer to join our Composition Modernization product team. We’re looking for a proven individual with a strong track record in strategic solution design, development, and deployment and is skilled in AI technologies and developer tooling including Model Context Protocol (MCP), agentic orchestration, A2A protocol, and large language model integration. As part of our team, the engineer will design, develop, and deploy AI-powered agents that automate end to end workflows and helping migrate communications from legacy systems into our modern platform at a quicker speed.

Requirements

Strong proficiency in programming languages such as Python, Go, Node.js, TypeScript, JavaScript, or Java
Strong Cloud Platform Experience (AWS & ROSA): Working experience with AWS services and Red Hat OpenShift Service on AWS (ROSA), including deploying and operating applications in these environments
Strong hands-on experience with AWS services including Lambda, S3, API Gateway, DynamoDB, RDS
Strong proficiency in Infrastructure as Code such as Terraform
Strong proficiency in using AI assisted tooling such as Copilot Agent mode, Gemini, Claude
Experience working with AI Agent & Core Services: Bedrock Agent, Agent Core
Experience with the Model Context Protocol (MCP) or similar tool-use frameworks for LLMs
Full Stack Development — hands-on experience building and delivering applications across the stack, including modern frontend frameworks (e.g., Angular, React, Vue.js etc) and backend services
Solid understanding of modern software development workflows including CI/CD, version control (Git), and code review practices
Strong proficiency with IDE ecosystems and developer tooling (e.g., VS Code extensions, CLI tools)
Familiarity with monitoring and observability tools (CloudWatch, Dynatrace, AWS XRay)
Strong problem-solving skills and ability to work independently as well as collaboratively
Excellent written and verbal communication skills

Nice To Haves

Hands-on experience building or customizing agentic AI workflows (e.g., multi-step autonomous agents, spec driven development, etc.)
Familiarity with LangGraph, A2A, Retrieval-Augmented Generation (RAG), Prompt Engineering, and Chunking techniques.

Responsibilities

Design, build, and maintain AI-driven orchestration pipelines that coordinate LLMs, connectors
Develop agentic and autonomous workflows using emerging AI capabilities (Copilot Studio, agentic orchestration patterns, MCP, A2A protocol) to enable self-directed task execution and multi-stop reasoning
Implement Model Context Protocol integrations to unify model access to enterprise systems, ensuring secure, governed, and scalable interactions between AI agents and organizational data.
Participate in code reviews and architectural discussions
Self-Driven Learning & Execution — Ability to independently research, learn, and implement new technologies and approaches with minimal direction; comfortable operating in ambiguity and driving work forward