The Mutual Group is seeking an AI Automation Engineer to design, build, and scale AI-assisted automation across IT engineering, infrastructure, and operations. This role emphasizes delivering reusable assets that raise productivity while maintaining secure, maintainable automation across the organization and its member insurers.
Location
Iowa (hybrid)
Salary
Base salary: $100,000 - $135,000 per year, depending on experience and location. In California, Connecticut, Massachusetts, New Jersey, New York, and Pennsylvania, the range is $110,000 - $140,000 per year.
Responsibilities
- Design, develop, test, and maintain AI-assisted automation components, scripts, integrations, workflows, and reusable engineering assets.
- Build automation that enhances software delivery, testing, documentation, release readiness, operational workflows, and employee productivity.
- Translate technical requirements and use cases into working AI-enabled solutions using APIs, scripts, cloud services, workflow tools, and AI development platforms.
- Create reusable templates, connectors, prompts, scripts, and implementation examples for adoption by other IT teams.
- Support proof-of-concept work and mature successful automation patterns into repeatable, production-ready capabilities.
- Develop 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 AI-enabled automation can simplify.
- Document usage patterns, reusable prompts, workflows, and enablement materials to help teams adopt AI tools responsibly and effectively.
- 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, governed manner.
- Contribute to reusable components for prompt handling, response validation, logging, monitoring, evaluation, and production support.
- 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.
- 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.
- Collaborate 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.
- 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.
Requirements
- 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 calls, 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.
- Proficiency in 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.
Technologies
- Python
- JavaScript/TypeScript
- PowerShell
- Bash
- Java
- .NET
- ChatGPT
- Microsoft Copilot
Benefits
- Competitive base salary plus incentive plans for eligible team members
- 401(K) retirement plan with company matching up to 6% of eligible salary
- Free basic life and AD&D, long-term disability and short-term disability insurance
- Medical, dental and vision plans
- Wellness incentives
- Generous time off including personal, holiday, and volunteer days
- Flexible work schedules and hybrid/remote options for eligible roles
- Educational assistance
Department
Information Technology
Job Description
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 reliability of engineering processes.
