AI Automation Engineer

Responsibilities

• 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.
• 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.
• 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.
• Document usage patterns, reusable prompts, workflows, and enablement materials that help teams adopt AI tools effectively and responsibly.
• Build AI‑enabled workflows that support coding, test generation, documentation, requirements analysis, code review, knowledge retrieval, and developer productivity.
• Partner with engineering and operations teams to identify repetitive work that can be simplified through AI‑enabled automation.
• Create operational runbooks, support documentation, and repeatable workflows for AI‑enabled operations use cases.

• 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/Type Script, Power Shell, Bash, Java, .NET, or similar languages.
• Working knowledge of CI/CD, test automation, Dev Sec Ops , 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.