Lead Architect - Azure & Agentic AI Solutions
Fractal Analytics16 days ago
Pune, India +3 moreStaff+
Responsibilities
- Own the end-to-end target architecture across data, AI/ML, GenAI, agent orchestration, APIs, integrations, observability, security, and user-facing applications.
- Determine the appropriate Azure deployment stack and define architecture principles, guardrails, non-functional requirements, and environment promotion and rollback patterns.
- Design agent architectures, orchestration patterns, tool boundaries, control flows, integration architectures, executable business workflows, and exception paths.
- Define identity, access, networking, secrets, data protection, content safety, prompt security, responsible AI, auditability, and enterprise governance controls.
- Lead architecture reviews, design walkthroughs, technical decision records, trade-off discussions, and stakeholder alignment with client and internal teams.
- Provide hands-on implementation guidance, reusable patterns, deployment standards, technical issue resolution, observability design, capacity planning, and cloud cost optimization.
- Produce target-state architecture and Azure deployment blueprints, integration and environment architectures, architecture decision records, engineering guardrails, and production-readiness recommendations.
Requirements
- 10+ years of experience in enterprise solution architecture, cloud architecture, platform engineering, or related technology leadership roles.
- Strong hands-on architecture experience with Microsoft Azure and enterprise deployment patterns.
- Proven experience designing distributed systems, APIs, microservices, event-driven architectures, containerized workloads, and cloud-native integrations.
- Strong understanding of GenAI and agentic AI architecture, including LLM orchestration, tool calling, RAG, state and memory patterns, evaluation, guardrails, and human approval mechanisms.
- Ability to combine conventional software services, AI/ML models, optimization engines, data pipelines, and agentic workflows in a coherent architecture.
- Strong knowledge of security, identity, networking, observability, CI/CD, infrastructure-as-code, and production operations in enterprise environments.
- Experience engaging with client architects, CIO/CTO organizations, cloud platform teams, security stakeholders, delivery teams, and engineering teams.
- Strong communication skills for explaining architecture trade-offs to technical and business stakeholders and driving decisions under real-world constraints.
- Preferred experience with Azure OpenAI, Azure AI Foundry, Azure Machine Learning, Databricks, AKS, Container Apps, API Management, Service Bus, Event Grid, Key Vault, Entra ID, and Azure Monitor.
- Preferred experience with LangGraph, Semantic Kernel, AutoGen, MLOps, LLMOps, model monitoring, prompt and agent evaluation, production AI governance, and relevant Azure architecture certifications or equivalent demonstrable experience.
- Exposure to supply chain, demand forecasting, planning, semiconductor, or high-tech industry solutions is preferred.
Tech Stack
AzureDatabricks
Categories
Solutions Engineering