AI Engineer Lead
2 days ago
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
 
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