Lead Architect of Agentic AI Systems
You'll spearhead the development, deployment, and maintenance of cutting-edge agentic AI systems that revolutionize enterprise operations. These intelligent agents will autonomously manage workflows, analyze real-time data, and embed decision-making across domains like finance, sales, and operations.
Key Responsibilities
* Design and lead the architecture of scalable, production-grade agentic AI systems.
* Develop 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.
* Evaluate and ensure observability and reliability through Azure Monitor, logging, and alerting frameworks.
* Define and enforce architecture patterns, reusable components, and governance standards.
* Conduct 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.
* Oversight of delivery timelines, quality benchmarks, and stakeholder communication.
* Promote 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
* Close collaboration 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).