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AI Automation Engineer

$100k - $135k

The Mutual Group

AI Automation Engineer

The AI Automation Engineer will develop AI-assisted automation, integrations, scripts, workflows, and reusable components that improve engineering productivity, testing, documentation, observability, incident response, and operational efficiency across The Mutual Group and its member insurance carriers. This is a hands-on engineering role for a practical builder who can use AI, automation, APIs, data, and modern engineering tools to simplify work, reduce manual effort, and improve the speed and quality of technology delivery.

This role will support the AI-First IT team by building automation capabilities that can be piloted, refined, and scaled across IT engineering, infrastructure, operations, and employee productivity use cases. The AI Automation Engineer will work closely with AI solutions engineers, architects, application teams, infrastructure and operations teams, data teams, security, risk governance, and business partners to deliver secure, reliable, and reusable automation assets.

The successful candidate will be curious, detail-oriented, and comfortable working in a fast-moving environment where new AI tools and automation patterns are being tested. This role requires strong engineering discipline, practical problem-solving, and the ability to balance experimentation with secure and maintainable implementation.

Work Arrangement:

  • Employees who live within 30 miles of the TMG home office are expected to follow a hybrid or in-office schedule. The initial training period may require additional in-office days.

Accountabilities:

  • Automation Development & Engineering
    • Design, build, test, and maintain AI-assisted automation components, scripts, integrations, workflows, and reusable engineering assets.
    • Develop automation that improves software delivery, testing, documentation, release readiness, operational workflows, and employee productivity.
    • Translate technical requirements and use cases into working solutions using APIs, scripts, cloud services, workflow tools, and AI-enabled development platforms.
    • Create reusable templates, connectors, prompts, scripts, and implementation examples that can be adopted by other IT teams.
    • Support proof-of-concept development and help mature successful automation patterns into repeatable, production-ready capabilities.
  • AI-Assisted Engineering & Productivity
    • Build AI-enabled workflows that support coding, test generation, documentation, requirements analysis, code review, knowledge retrieval, and developer productivity.
    • Configure and support productivity use cases using tools such as ChatGPT, Microsoft Copilot, and related AI assistants.
    • Develop practical automation for summarization, classification, document processing, ticket analysis, workflow routing, meeting support, and knowledge assistance.
    • Partner with engineering and operations teams to identify repetitive work that can be simplified through AI-enabled automation.
    • Document usage patterns, reusable prompts, workflows, and enablement materials that help teams adopt AI tools effectively and responsibly.
  • Integration, Data & Platform Support
    • Integrate automation capabilities with enterprise applications, APIs, data sources, document repositories, service management platforms, collaboration tools, and cloud services.
    • Support AI solution development using Generative AI patterns such as LLMs, embeddings, prompt engineering, retrieval-augmented generation, semantic search, and enterprise knowledge integration.
    • Assist with Agentic AI patterns, including tool and function calling, workflow orchestration, human-in-the-loop controls, guardrails, monitoring, and safe execution.
    • Use Model Context Protocol (MCP) or similar approaches to connect AI systems with enterprise tools, APIs, data sources, and workflow actions in a secure and governed manner.
    • Contribute to reusable components for prompt handling, response validation, logging, monitoring, evaluation, and production support.
  • IT Operations & Observability Automation
    • Build automation that supports observability, incident summarization, root cause analysis, alert enrichment, runbook automation, service management, and operational productivity.
    • Partner with Infrastructure and IT Operations teams to identify opportunities for predictive monitoring, automated remediation, knowledge retrieval, and workflow simplification.
    • Support integration with monitoring, logging, ticketing, collaboration, and service management tools.
    • Create operational runbooks, support documentation, and repeatable workflows for AI-enabled operations use cases.
    • Help measure improvements in manual effort reduction, cycle time, documentation quality, incident response, operational efficiency, and reuse.
  • Security, Quality & Production Readiness
    • Apply secure-by-design and privacy-by-design practices in all automation and AI-enabled workflows.
    • Follow enterprise standards for identity and access management, sensitive data handling, logging, monitoring, output validation, and responsible AI usage.
    • Work with Security, Data, Architecture, and AI & Technology Risk Governance teams to ensure automation solutions meet auditability, reliability, and compliance expectations.
    • Test automation components for accuracy, performance, resilience, maintainability, and operational readiness.
    • Identify risks, dependencies, support needs, and production readiness gaps early in the delivery process.
  • Collaboration, Documentation & Continuous Improvement
    • Work closely with AI solutions engineers, architects, product partners, business teams, contractors, vendors, and system integration partners to deliver priority automation initiatives.
    • Participate in design reviews, code reviews, troubleshooting, testing, and implementation planning.
    • Document solution designs, configuration steps, reusable patterns, operational procedures, and lessons learned.
    • Contribute to technical playbooks, reference examples, and enablement materials that help broader IT teams adopt AI-assisted automation.
    • Continuously improve automation quality, reliability, documentation, observability, security, and reuse.

Qualifications:

  • 4+ years of technology experience across software engineering, automation, scripting, integration, cloud, data, platform engineering, IT operations, or enterprise technology delivery.
  • 2+ years of experience with AI, machine learning, automation, advanced analytics, intelligent platforms, developer productivity tools, or emerging technology capabilities.
  • Hands-on experience with scripting, workflow automation, APIs, integrations, cloud services, and modern engineering tools.
  • Familiarity with Generative AI patterns, including LLMs, embeddings, prompt engineering, RAG, semantic search, summarization, classification, and enterprise knowledge retrieval.
  • Familiarity with Agentic AI concepts such as tool/function calling, orchestration, human-in-the-loop workflows, guardrails, monitoring, and safe deployment practices.
  • Familiarity with Model Context Protocol (MCP) or similar methods for connecting AI systems to enterprise tools, APIs, data sources, and workflows.
  • Experience with Python, JavaScript/TypeScript, PowerShell, Bash, Java, .NET, or similar languages.
  • Working knowledge of CI/CD, test automation, DevSecOps, observability, service management, identity, cybersecurity, and privacy practices.
  • Experience building automation components, integrations, reusable scripts, workflow tools, or developer productivity solutions.
  • Experience with ChatGPT, Microsoft Copilot, or similar enterprise AI productivity platforms preferred.
  • Experience working in regulated environments with security, privacy, auditability, operational readiness, and compliance expectations preferred.
  • Bachelor's degree in Computer Science, Engineering, Information Systems, Data Science, or related field preferred, or equivalent practical experience.

Pay Range:

  • $100,000 - $135,000 annual base salary depending on experience, qualifications, and geographic location
  • $110,000 - $140,000 annual base salary depending on experience, qualifications, and geographic location in CA, CT, MA, NJ, NY, and PA

Benefits:

  • Competitive base salary plus incentive plans for eligible team members
  • 401(K) retirement plan that includes a company match of up to 6% of your eligible salary
  • Free basic life and AD&D, long-term disability and short-term disability insurance
  • Medical, dental and vision plans to meet your unique healthcare needs
  • Wellness incentives
  • Generous time off program that includes personal, holiday and volunteer paid time off
  • Flexible work schedules and hybrid/remote options
Vacancy posted 2 hours ago
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