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Senior Terraform Developer Jobs Near Me

Payments Tech - Java Developer

Columbus, OH · On-site

$49.25 - $63.75/hr

We are seeking a Senior Programmer/Analyst with GCP experience to support the development and ... Experience with Infrastructure as Code (Terraform preferred). * Ability to balance development and ...

New

Payments Tech - Java Developer

Columbus, OH · On-site

$48 - $62/hr

We are seeking a Senior Programmer/Analyst with GCP experience to support the development and ... Experience with Infrastructure as Code (Terraform preferred). * Ability to balance development and ...

New

... Azure DevOps (e.g., Pipelines/Releases/Boards) * High proficiency with Terraform and Ansible ... Act as the senior voice with the engineering team to establish standards, share best practices, and ...

UK Sr Software Engineer

Columbus, OH · On-site

$115K - $152K/yr

... and DevOps concepts ● Experience working with customers/end-users Preferred Experience ... Infrastructure automation technologies such as Kubernetes, Helm and Terraform. * Developing ...

Senior IT Systems Engineer

Ashville, OH · On-site

$95K - $130K/yr

ABOUT THE JOB Anduril is seeking an Senior IT Systems Engineer to build and maintain our tech stack ... Proficiency in infrastructure-as-code (IaC) tools such as Terraform, Ansible, or CloudFormation.

About the Job Anduril is seeking a Senior IT Systems Engineer to build and maintain the tech stack ... Proficiency in IaC tools such as Terraform, Ansible, or CloudFormation. * Experience with ...

New

Senior IT Systems Engineer

Ashville, OH · On-site

$95K - $130K/yr

The Senior IT Systems Engineer will build and maintain the tech stack supporting mission-critical ... as Terraform, Ansible, or CloudFormation. • Collaborate with development, security, and ...

React Developer

Columbus, OH · On-site

$100K - $116K/yr

React Developer Location: Columbus, OH- Looking for only Nearby as F2F is require. W2 Candidates ... Terraform as well - NICE TO HAVE skills Any previous design experience is a big plus - The more Sr ...

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Senior Terraform Developer information

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$80.3K

$163.5K

How much do senior terraform developer jobs pay per year?

As of Aug 21, 2026, the average yearly pay for senior terraform developer in the United States is $80,287.00, according to ZipRecruiter salary data. Most workers in this role earn between $41,500.00 and $103,000.00 per year, depending on experience, location, and employer.

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A map of the United States highlighting the number of Senior Terraform Developer job openings by state according to ZipRecruiter. The image is accompanied by a detailed chart listing the number of Senior Terraform Developer job openings in each state, with California having the most at 2 and Hawaii the least at 0.

Senior Software Engineer - Platform & Agentic AI Engineering

The Hartford

Columbus, OH

$118K - $156K/yr

Full-time

Posted 14 days ago


The Hartford rating

8.8

Company rating: 8.8 out of 10

Based on 121 frontline employees who took The Breakroom Quiz

56th of 311 rated insurance


Job description

Senior Staff Software Engineer - IE07HE

We're 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 - and to help others accomplish theirs, too. Join our team as we help shape the future.

This requisition hires Senior AI Engineers who will:

Design and deliver productiongrade Agentic AI systems using Google ADK, Anthropic MCP, LangGraph/LangChain, and modern Agentic protocols. Build secure, scalable AI platform capabilities with strong engineering fundamentals in Python/Typescript, Terraform, and GCP. Enable enterprise adoption of AI by creating reusable frameworks, APIs, and platform capabilities aligned with engineering standards, compliance needs, and modern cloud patterns.

Overview

The Senior AI Engineer will architect, build, and operationalize advanced AI and multi-agent solutions leveraging RAG, GraphRAG, Agentic AI frameworks, and enterprisegrade 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 AlloyDB's AI/Agentic capabilities-including vector indexing, embedding support, and tight integration with Vertex AI-as 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.

The role additionally requires deep, hands-on experience building and extending agent harnesses-the runtime scaffolding that orchestrates the agent execution loop, tool invocation, dynamic context-window assembly, sub-agent delegation, and guardrail and permission enforcement-together with production expertise in LangChain and LangGraph.

Fluency in spec-driven, agentic development frameworks such as GitHub Spec-Kit, OpenSpec, and BMAD-METHOD, used to translate intent into executable specifications and orchestrate AI-assisted delivery at enterprise scale.

Responsibilities

AI/Agentic System Architecture & Development

  • Design and implement Agentic AI solutions using Google ADK, LangGraph, LangChain, and Agent Engine.
  • Build and extend agent harnesses, implementing the agent execution loop, tool-call orchestration, dynamic prompt and context assembly, sub-agent delegation, streaming, token-budget management, and hook and guardrail enforcement.
  • Engineer advanced LangChain and LangGraph orchestration, including LCEL chains, stateful graphs, checkpointing, human-in-the-loop workflows, memory, retrievers, callbacks, and LangSmith tracing and evaluation.
  • Build advanced RAG and GraphRAG pipelines, vector retrieval systems, and knowledgegraph-augmented 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
    • Multistep 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
    • ACIDcompliant 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.

Spec-Driven & Agentic Development

  • Drive spec-driven development (SDD) using frameworks such as GitHub Spec-Kit, OpenSpec, and BMAD-METHOD, translating product intent into executable specifications, plans, and agent-ready task breakdowns.
  • Establish specification-first review gates and living change proposals that align human engineers and AI agents before implementation begins.

Security, Governance & Session Management

  • Implement enterprise-grade security for agents including:
    • OAuth and SSO flows
    • IAM roles, service accounts, leastprivilege design
    • Secure MCP tool access, command permissioning, and input validation
  • Architect safe sessionbased 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 and frameworks-including Claude Code, GitHub Copilot, AWS Kiro, GitHub Spec-Kit, OpenSpec, and BMAD-METHOD-and integrate them into engineering workflows.
  • Partner with architects, data engineers, and platform teams to implement crossdomain AI capabilities.
  • Document architecture patterns, reusable code modules, and standards for MCP/Agentic development.

Qualifications

Experience

  • 6-8 years in software engineering, including 2+ years in GenAI, multi-agent, or LLM systems.
  • Proven delivery of at least one productiongrade 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) - tools, capabilities, memory, session orchestration, security
    • Google ADK Agentic Protocols - agents, workflows, context management
    • LangChain & LangGraph - LCEL chains, agents, tools, memory, retrievers, stateful graph orchestration, checkpointing, human-in-the-loop control, and LangSmith tracing and evaluation
    • Agent harness engineering - agent execution loops, tool-call orchestration, context and prompt assembly, sub-agent delegation, streaming, token-budget management, and hook and guardrail enforcement

Spec-Driven & Agentic Development Frameworks

  • Hands-on experience with spec-driven development (SDD) workflows and tooling, including GitHub Spec-Kit (specify, plan, tasks, implement), OpenSpec (change proposals and living specifications), and BMAD-METHOD (agentic planning with specialized agent roles)
  • Proven ability to decompose product intent into executable specifications, structured plans, and agent-ready task breakdowns that align human and AI contributors before code is written
  • Familiarity with greenfield and brownfield delivery driven by multi-agent planning, context engineering, and specification-first review gates

Databases & Agent Memory Stores

  • Handson 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

  • Bachelor's or Master's 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 Hartford's 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

About Us|Our Culture|What It's Like to Work Here|Perks & Benefits


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Hartford logo

About Hartford

Sourced by ZipRecruiter

Hartford Financial Services Group, widely recognized as The Hartford, is a renowned company based in Hartford, CT, US. Established in 1810, it has evolved into an industry leader in the insurance and financial services sector, proudly serving more than one million businesses in the US. The Hartford is committed to offering a gamut of insurance products that include homeowners, automobile, and business insurance as well as employee benefits and mutual funds. The company’s core values revolve around customer-focused innovations, diversity and inclusion, and ethical dealings that have earned them a customer-centric reputation. This shapes their mission which revolves around aiding their clients to overcome unforeseen obstacles and enhancing their wealth over time. Among the company's noted accomplishments is being consistently listed among the World's Most Ethical Companies, a testament to their unwavering commitment towards responsible business practices.

Industry

Finance and insurance

Company size

10,000+ Employees

Headquarters location

Hartford, CT, US

Year founded

1810

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