Automation Engineer

Automation Engineer

Summary / Position Purpose

The Automation Engineer designs, builds, and deploys intelligent automation solutions and AI-powered agents that streamline business processes, reduce manual effort, and accelerate operational efficiency across the enterprise. This role combines strong Python development skills with hands-on experience in agentic AI-building autonomous systems that can reason, plan, execute multi-step tasks, and integrate with enterprise platforms.

Working closely with AI, BI, Engineering, Operations, and business teams, this role identifies automation opportunities, develops scalable solutions, and ensures reliable, production-grade deployment.

Reporting to the Director of AI & Data Strategy, this is a hands-on technical role focused on delivering measurable business impact through intelligent automation aligned with the enterprise-wide technology strategy.

Essential Duties, Functions and/or Responsibilities

Automation Development & Deployment

• Design, develop, and maintain automation solutions that streamline workflows across business functions including Sales, Operations, Customer Service, and Finance. (Python, PowerShell, C#, Azure Logic Functions, Workato, etc.)
• Build and deploy production-grade scripts, APIs, and scheduled jobs that reduce manual effort and improve data accuracy, speed, and consistency.
• Develop reusable automation frameworks and libraries to accelerate future development and ensure code maintainability.
• Implement error handling, logging, monitoring, and alerting to ensure automation reliability and rapid issue resolution.
• Manage the full lifecycle of automation projects from requirements gathering through deployment and ongoing optimization.

Agentic AI & Intelligent Automation

• Design and build agentic AI systems that autonomously reason, plan, and execute multi-step tasks with minimal human intervention.
• Develop AI agents and copilots using LLMs, prompt engineering, retrieval-augmented generation (RAG), and agent orchestration frameworks.
• Implement memory systems, tool-calling capabilities, and feedback loops that enable agents to adapt and improve over time.
• Monitor agent performance including accuracy, latency, cost efficiency, and reliability, with continuous optimization.

Requirements

Copilot Studio, Azure AI Foundry, Power Automate, Logic Apps, M365 AI, Azure SQL, Fabric, Claude CLI, Python, T-SQL, SQL, JavaScript, JSON, HTML, C#, .NET.