Lead AI Engineer / AI Solution Architect – Azure AI Foundry
Experience
8 – 10 years
Level
Lead / Architect
Location
Delhi / Mumbai / Bangalore (India)
Employment Type
Full-time
Primary Skills
Azure AI Foundry, RAG, AI Agents, AI / ML
Role Summary
We are looking for a Lead AI Engineer / AI Solution Architect to define and drive the technical vision for enterprise Generative AI and agentic AI solutions on Azure AI Foundry. You will architect end-to-end RAG and multi-agent platforms, set engineering standards, lead and grow a team of AI engineers, and partner with senior client stakeholders to deliver measurable business outcomes.
Key Responsibilities
- Own the end-to-end architecture of enterprise GenAI platforms on Azure AI Foundry, covering RAG, multi-agent systems, ML pipelines, security, and integration.
- Define reference architectures, reusable accelerators, and best practices for RAG, agents, evaluation, and LLMOps across engagements.
- Lead the design of complex multi-agent workflows with orchestration, memory, human-in-the-loop, and enterprise tool / MCP integration.
- Establish governance for responsible AI: guardrails, content safety, data privacy, compliance, model risk, and audit.
- Drive model strategy: selection among Azure OpenAI and open-source models, fine-tuning, cost-performance trade-offs, and capacity planning.
- Define evaluation, observability, and monitoring strategy for AI systems in production (quality, drift, latency, cost, safety).
- Lead, mentor, and grow a team of AI engineers; set technical direction, review designs, and ensure delivery quality.
- Partner with client CXO / senior stakeholders in solutioning, discovery workshops, proposals, estimations, and technical presales.
- Evaluate emerging AI technologies and drive POCs that convert into scalable offerings.
Required Skills & Experience
- 8 – 10 years of total experience in software / data / AI engineering, with at least 3 – 4 years architecting and delivering Generative AI solutions in production.
- Deep expertise in Azure AI Foundry (model catalog, Agent Service, evaluations, tracing, safety, governance) and the wider Azure AI stack.
- Demonstrated experience architecting large-scale RAG systems (hybrid retrieval, graph / agentic RAG, multimodal, multi-tenant, access-controlled).
- Demonstrated experience architecting multi-agent systems with Azure AI Foundry and frameworks such as Semantic Kernel, LangGraph, or AutoGen.
- Strong AI/ML foundation: classical ML, deep learning, NLP / LLMs, fine-tuning, evaluation, and MLOps on Azure Machine Learning or equivalent.
- Strong Azure architecture skills: networking (VNet, Private Link), identity (Entra ID, managed identity), AKS / Container Apps, API Management, Cosmos DB, Key Vault, Monitor.
- Expert-level Python and strong software architecture / design-pattern knowledge; experience with CI/CD and Infrastructure as Code.
- Track record of leading teams, owning delivery outcomes, and managing technical risk.
- Excellent client-facing skills, including presales, proposal writing, and executive presentations.
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Good to Have
- Azure certifications (AI-102, DP-100, AZ-305, or AZ-400).
- Experience with fine-tuning (LoRA / PEFT), distillation, and small language models.
- Experience in Microsoft Fabric, Databricks, or modern data platform architecture.
- Experience in regulated industries (BFSI, healthcare, public sector) and associated compliance needs.
- Published work, patents, conference talks, or community contributions in AI.
Soft Skills
- Strategic thinking with the ability to connect AI capabilities to business value.
- Strong leadership, mentoring, and cross-functional collaboration.
- Clear and persuasive communication with both technical and executive audiences.
Education
B.E. / B.Tech / M.E. / M.Tech / MCA / M.Sc in Computer Science, Data Science, AI/ML, or a related field. Advanced degree preferred.
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