Lead AI Engineer

About The Role

You’ll lead the architecture, development, and deployment of next-generation agentic AI systems that transform enterprise operations. These intelligent agents will autonomously orchestrate workflows, analyze real-time data, and embed decision-making across domains like finance, sales, and operations. You’ll guide cross-functional teams, mentor engineers, and ensure technical excellence across all stages of delivery. Microsoft AI Foundry will be a key platform for agent development, and Copilot Studio may be used optionally for few use cases.

Day-to-Day Work Responsibilities

• Architect and lead development of scalable, production-grade agentic AI systems.
• Design serverless, event-driven workflows using Azure Functions, Logic Apps, and Power Automate.
• Build and optimize ML models for predictive analytics, anomaly detection, and recommendations using Azure ML, Databricks, and Python.
• Integrate agents with enterprise platforms such as SAP HANA, Salesforce, Snowflake, Kafka, and UiPath.
• Ensure observability and reliability through Azure Monitor, logging, and alerting frameworks.
• Define and enforce architecture patterns, reusable components, and governance standards.
• Lead code reviews, technical design sessions, and agile ceremonies.
• Leverage Microsoft AI Foundry to build and deploy agents that meet enterprise-grade standards.
  
  

Leadership Responsibilities

• Mentor and coach junior engineers, fostering a culture of innovation and technical excellence.
• Drive cross-team collaboration and alignment on agentic AI strategy and execution.
• Own delivery timelines, quality benchmarks, and stakeholder communication.
• Champion best practices in DevOps, CI/CD, and model lifecycle management.
• Stay ahead of trends in AI, machine vision, and IoT to guide strategic decisions.
  
  

Cross-Functional Collaboration

You Will Work Closely With

• Data Scientists & ML Engineers – for model development and integration
• Product Managers & UX Designers – aligning agent capabilities with user needs
• Enterprise Architects & DevOps Engineers – ensuring scalability and deployment efficiency
• Security & Compliance Teams – meeting regulatory and governance requirements
• Business Stakeholders & SMEs – defining use cases and validating outcomes
• Change Management & Enablement Teams – supporting adoption and training efforts
  
  

Technology & Tools

• Languages & Platforms: Python, Power Apps, Power Automate, Databricks, Snowflake
• Enterprise Systems: SAP HANA, Kafka, UiPath
• AI Platforms: Microsoft AI Foundry (highly preferred), Copilot Studio (optional)
• Cloud & ML Tools: Azure Machine Learning, Azure DevOps, GitHub
• Data & Observability: Vector Databases, Azure Monitor
• Vision & IoT: Azure IoT Hub, OpenCV, TensorFlow, PyTorch (for edge and vision-based agents)
  
  

What You Bring With You

• Proven experience leading AI engineering teams and delivering enterprise-grade solutions
• Strong technical depth in AI/ML, cloud platforms, and agentic system design
• Ability to navigate ambiguity, drive clarity, and influence across functions
• Passion for building transformative AI systems that solve meaningful problems
  
  

Our Commitment to a Culture of Inclusion & Belonging

Ecolab is committed to fair and equal treatment of associates and applicants and furthering the principles of Equal Opportunity to Employment. We will recruit, hire, promote, transfer and provide opportunities for advancement based on individual qualifications and job performance in all matters affecting employment, compensation, benefits, working conditions, and opportunities for advancement. Ecolab will not discriminate against any associate or applicant for employment because of race, religion, color, creed, national origin,citizenship status, sex, sexual orientation, gender identity and expressions, genetic information, marital status, age, or disability.

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