Lead AI Engineer

Lead AI Engineer Role Overview: We’re seeking a Lead AI Engineer to spearhead the design and implementation of intelligent agents on Azure’s AI Foundry platform. You will build, deploy, and maintain custom LLM-driven agents (using Semantic Kernel or similar SDKs) that orchestrate multi-step workflows. Your work will be central to delivering a production-grade, high-throughput AI system that integrates Azure Cognitive Services, Azure ML, and Foundry Agent Service. Key Responsibilities: Develop and maintain AI agents using Semantic Kernel (or equivalent) to define “skills” and prompt workflows. Integrate LLMs (Azure OpenAI or equivalent) with Azure AI Foundry Agent Service to create, version, and monitor multi-agent workflows. Build and deploy custom ML models (e.g., Computer Vision classifier) on Azure Machine Learning, ensuring scalable, low-latency inference. Implement agent “tool” functions that call Azure services (Cognitive Services OCR, Azure Functions, Cosmos DB, Service Bus) via secure, managed identities. Collaborate with Data Engineers and Backend Engineers to ensure smooth data flow (e.g., ingesting part specs, storing results, orchestrating events). Implement automated logging, tracing, and performance monitoring for agent execution (leveraging Foundry’s AgentOps features and Application Insights). Iterate quickly: prototype new model architectures or prompt designs, validate with sample data, and roll out improvements in CI/CD pipelines. Partner with Domain Engineers to translate manufacturability rules into agent logic and help refine model training data. Required Skills & Qualifications: Bachelor’s or Master’s in Computer Science, AI/ML, or related field; 5+ years of hands-on ML/AI engineering experience. Deep experience with Azure ML (model training, endpoint deployment, and model management). Proficiency in Semantic Kernel or similar LLM-agent SDK/platform (LangChain, AutoGen, CrewAI), with a strong grasp of prompt engineering, function-calling patterns, and multi-agent orchestration. Familiarity with Azure AI Foundry Agent Service (demonstrated ability to build and deploy agents as microservices). Knowledge of MCP Strong Python skills and experience building production-grade ML pipelines (data preprocessing, model training, inference code). Experience integrating Computer Vision models (TensorFlow, PyTorch) with Azure Cognitive Services OCR or custom CV pipelines. Proficient with Azure Cognitive Services, especially OCR/Document Intelligence APIs. Solid understanding of cloud-native security (Managed Identities, Key Vault) and best practices for secure model serving. Experience with observability tools (Application Insights, Foundry AgentOps) to monitor agent performance and debug end-to-end flows. Excellent problem-solving, communication, and collaboration skills—able to work cross-functionally in a fast-paced startup environment.