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Sr Staff Software Engineer

MSCCN - Morristown, NJ

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Job Description

Senior Staff Software Engineer - IE07HE Weu2019re determined to make a difference and are proud to be an insurance company that goes well beyond coverages and policies. Working here means having every opportunity to achieve your goals u2013 and to help others accomplish theirs, too. Join our team as we help shape the future. Overview The Senior AI Engineer will architect, build, and operationalize advanced AI and multi-agent solutions leveraging RAG , GraphRAG , Agentic AI frameworks , and enterpriseu2011grade cloud engineering. A key requirement is robust, practical experience implementing MCP and ADK Agentic Protocols , with a solid understanding of: + Agent memory + Session and context lifecycle management + Tooling interfaces + Secure capability boundaries + Permissions and role enforcement Additionally, candidates must have hands-on experience with AlloyDBu2019s AI/Agentic capabilities u2014including vector indexing, embedding support, and tight integration with Vertex AIu2014as well as strong fundamentals in PostgreSQL / Postgres RDS for building retrieval systems, agent memory stores, and structured context-management layers. The engineer must demonstrate strong foundational engineering skills in Python or Typescript, IaC (Terraform), DevOps pipelines, and secure distributed system design using GCP services such as Vertex AI, Cloud Run, Cloud Storage, and AlloyDB. Responsibilities AI/Agentic System Architecture & Development + Design and implement Agentic AI solutions using Google ADK, LangGraph, LangChain, and Agent Engine. + Build advanced RAG and GraphRAG pipelines, vector retrieval systems, and knowledgeu2011graphu2013augmented reasoning. Implement MCP-compliant agents with capability registration, secure tool invocation, memory storage, and session state management. + Apply deep knowledge of Agentic Protocol design (ADK & MCP), such as: + Agent memory and conversation state + Tool authorization + Multiu2011step workflows and orchestration + Session boundary and identity controls + Leverage AlloyDB and PostgreSQL/RDS for: + Vector storage and hybrid search + Agent memory persistence, session management, and state recovery + Structured prompt scaffolding and fact retrieval + ACID compliant transactional reasoning layersu2011compliant transactional reasoning layers + Develop scalable AI microservices using Python/Typescript, Cloud Run, Vertex AI, and event-driven components. + Optimize model inference, retrieval latency, and overall system performance. Security, Governance & Session Management + Implement enterprise-grade security for agents including: + OAuth and SSO flows + IAM roles, service accounts, least privilege designu2011privilege design + Secure MCP tool access, command permissioning, and input validation + Architect safe sessionu2011based AI interactions with proper expiration, auditing, and context isolation. + Ensure compliance with enterprise governance, Responsible AI requirements, and platform guardrails. Platform Engineering, IaC & DevOps + Use Terraform to build GCP infrastructure for AI workloads, vector stores, knowledge graphs, and orchestration services. + Build CI/CD pipelines for model deployments and agent lifecycle automation. + Implement observability, monitoring, and logging for AI service health. Innovation & Collaboration + Evaluate emerging tools like Claude Code, GitHub Copilot, AWS Kiro and integrate them into engineering workflows. + Partner with architects, data engineers, and platform teams to implement crossu2011domain AI capabilities. + Document architecture patterns, reusable code modules, and standards for MCP/Agentic development. Qualifications Experience + 6u20138 years in software engineering, including 2+ years in GenAI, multi-agent, or LLM systems. + Proven delivery of at least one productionu2011grade AI or Agentic system, preferably involving RAG or GraphRAG. Technical Expertise Core Engineering + Strong engineering fundamentals in Python and/or Typescript. Agentic AI & Protocols + Deep, practical experience with: + MCP (Model Context Protocol) u2014 tools, capabilities, memory, session orchestration, security + Google ADK Agentic Protocols u2014 agents, workflows, context management Databases & Agent Memory Stores + Handsu2011on experience with AlloyDB , including: + Vector indexing / pgvector + AI inference acceleration and Vertex AI integration + Building agent memory and retrieval layers + Transactional context management for Agentic systems + Strong PostgreSQL/Postgres RDS fundamentals , including: + Schema design for knowledge retrieval + Query optimization + Hybrid search patterns + Durable storage for AI session and memory state Cloud & Platform Skills + Experience with: + Vertex AI (Model Garden, Embeddings, Vector Search, Generative AI APIs) + GCP Cloud Run, AlloyDB, Cloud Storage, Secret Manager + Terraform / IaC + CI/CD automation, containerization, environment provisioning + OAuth, SSO, IAM roles/policies, service account management Additional + Experience with AI coding tools (Claude Code, GitHub Copilot, AWS Kiro). + Strong understanding of LLM safety, governance, context window management, and prompt engineering. Preferred Certifications + GCP Professional Cloud Architect + GCP Professional Machine Learning Engineer Education + Bacheloru2019s or Masteru2019s in Computer Science, Engineering, or related field. This role will have a Hybrid work schedule, with the expectation of working in an office (Columbus, OH, Chicago, IL, Hartford, CT or Charlotte, NC) 3 days a week (Tuesday through Thursday). Candidates must be authorized to work in the US without company sponsorship. The company will not support the STEM OPT I-983 Training Plan endorsement for this position. Compensation The listed annualized base pay range is primarily based on analysis of similar positions in the external market. Actual base pay could vary and may be above or below the listed range based on factors including but not limited to performance, proficiency and demonstration of competencies required for the role. The base pay is just one component of The Hartfordu2019s total compensation package for employees. Other rewards may include short-term or annual bonuses, long-term incentives, and on-the-spot recognition. The annualized base pay range for this role is: $127,600 - $191,400 Equal Opportunity Employer/Sex/Race/Color/Veterans/Disability/Sexual Orientation/Gender Identity or Expression/Religion/Age

Created: 2026-03-23

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