Senior AI Architect: Agentic & Multi‑Agent Systems

The Hartford; Columbus (OH); Hybrid; USD 128,000 - 191,000; Full time

Benefits offered by this job

Hybrid work schedule

Office presence in multiple cities

Job summary

The Hartford is seeking a Senior AI Engineer to architect and operationalize Agentic AI systems in a hybrid setup. You will design production‑grade AI solutions using ADK, MCP, LangChain, and LangGraph, with strong focus on memory, context management, and secure tool usage.

Expect collaboration across security, governance, and platform engineering teams to deliver scalable, enterprise‑grade solutions. You will contribute to RAG/GraphRAG pipelines, vector storage, and knowledge graphs, while

Qualifications

• 6–8 years in software engineering with 2+ years in GenAI, multi‑agent, or LLM systems
• Proven delivery of production‑grade AI or Agentic systems (RAG/GraphRAG)
• Strong fundamentals in Python and/or Typescript
• Hands‑on experience with AlloyDB’s AI/Agentic capabilities and Vertex AI
• Solid PostgreSQL/Postgres RDS knowledge for retrieval and memory layers
• Experience building scalable AI microservices and secure distributed systems

Responsibilities

• Design and implement Agentic AI solutions using Google ADK, LangGraph, LangChain, and Agent Engine
• Build and extend agent harnesses, orchestration, memory, and safety guardrails
• Develop advanced LangChain/LangGraph orchestration including stateful graphs and checkpointing
• Create scalable RAG and GraphRAG pipelines and knowledge graphs
• Ensure security, governance, and session management for enterprise AI systems

Skills

Python

Typescript

Terraform

GCP

PostgreSQL

Agentic AI

Security

Education

Bachelor’s or Master’s in CS/Engineering

Tools

LangChain

LangGraph

ADK

MCP

AlloyDB

Vertex AI

pgvector

Cloud Run

Terraform

Job description

The Hartford is seeking a Senior AI Engineer to architect and operationalize Agentic AI systems in a hybrid setup. You will design production‑grade AI solutions using ADK, MCP, LangChain, and LangGraph, with strong focus on memory, context management, and secure tool usage.

Expect collaboration across security, governance, and platform engineering teams to deliver scalable, enterprise‑grade solutions. You will contribute to RAG/GraphRAG pipelines, vector storage, and knowledge graphs, while