Lead AI Engineer

About the Role

We are seeking a dynamic Lead AI Engineer to spearhead the architecture, development, and deployment of cutting-edge agentic AI systems. This role is instrumental in transforming enterprise operations by creating intelligent agents capable of autonomously orchestrating complex workflows, analyzing real-time data, and embedding critical decision-making capabilities across diverse domains such as finance, sales, and operations. You will be responsible for guiding cross-functional teams, mentoring fellow engineers, and ensuring the highest standards of technical excellence throughout the entire delivery lifecycle. A key platform for agent development will be Microsoft AI Foundry, with Copilot Studio available for optional use in specific scenarios.

Day-to-Day Work Responsibilities

• Architect and lead the development of scalable, production-grade agentic AI systems.
• Design and implement serverless, event-driven workflows utilizing Azure Functions, Logic Apps, and Power Automate.
• Build and optimize machine learning models for predictive analytics, anomaly detection, and recommendation engines using Azure ML, Databricks, and Python.
• Integrate intelligent agents with core enterprise platforms including SAP HANA, Salesforce, Snowflake, Kafka, and UiPath.
• Ensure robust observability and reliability through comprehensive monitoring with Azure Monitor, effective logging, and alerting frameworks.
• Define, implement, and enforce critical architecture patterns, reusable components, and stringent governance standards.
• Lead crucial code reviews, technical design sessions, and facilitate agile ceremonies to maintain project momentum and quality.
• Leverage Microsoft AI Foundry to build and deploy agents that consistently meet enterprise-grade standards for performance and security.

Leadership Responsibilities

• Mentor and coach junior engineers, cultivating an environment of innovation and technical mastery.
• Drive effective cross-team collaboration and ensure alignment on the strategic vision and execution of agentic AI initiatives.
• Take ownership of delivery timelines, stringent quality benchmarks, and clear stakeholder communication.
• Champion best practices across DevOps, Continuous Integration/Continuous Deployment (CI/CD), and comprehensive model lifecycle management.
• Proactively stay informed about emerging trends in Artificial Intelligence, machine vision, and the Internet of Things (IoT) to inform strategic decision-making.

Cross-Functional Collaboration

You will collaborate closely with:

• Data Scientists & ML Engineers: For model development, refinement, and seamless integration.
• Product Managers & UX Designers: To ensure agent capabilities align precisely with user needs and enhance user experience.
• Enterprise Architects & DevOps Engineers: To guarantee scalability, deployment efficiency, and infrastructure robustness.
• Security & Compliance Teams: To adhere to all regulatory mandates and governance requirements.
• Business Stakeholders & SMEs: To define impactful use cases and rigorously validate outcomes.
• Change Management & Enablement Teams: To facilitate smooth adoption and comprehensive 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 successfully delivering enterprise-grade solutions.
• Strong technical depth in AI/ML, cloud platforms, and the design of agentic systems.
• Demonstrated ability to navigate ambiguity, drive clarity in complex situations, and influence stakeholders across various functions.
• A genuine passion for building transformative AI systems that address and solve meaningful, real-world problems.