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

Key skills/competency

• AI Engineering
• Agentic AI
• Azure Cloud Platform
• Python Programming
• Machine Learning
• Scalable Systems
• Technical Leadership
• DevOps Practices
• Predictive Analytics
• Data Integration