About this role
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.