Description

In this high-visibility staff role based out of our Chennai engineering center, you will serve as the primary architecture authority bridging complex data pipelines with production agentic execution. You will hold architectural ownership over solution designs, sequence diagrams, and Architecture Decision Records (ADRs) while retaining the hands-on technical depth to debug distributed systems and write mission-critical code. Collaborating daily with US engineering peers and product stakeholders, you will shape how autonomous agents orchestrate work across the enterprise using open, secure protocols.
 

Key Exciting Responsibilities

• End-to-End Solution Architecture: Own the full architectural lifecycle for AI and data ecosystems—from source-system ingestion through Databricks transformation, retrieval layers, and model serving, to user-facing APIs and autonomous agents.
• Databricks Platform Leadership: Architect workspaces, compute policies, and Unity Catalog governance. Design scalable batch and streaming pipelines following the Medallion architecture (Bronze, Silver, Gold), optimizing Apache Spark and Delta Lake workloads for extreme throughput and cost efficiency.
• Agentic Workflows & MCP Orchestration: Architect agentic AI solutions using frameworks such as LangGraph, LangChain, or Semantic Kernel. Establish enterprise standards for designing, securing, and operating servers and clients built on the Model Context Protocol (MCP).
• Azure AI & RAG Engineering: Direct the implementation of high-performance RAG pipelines across the Azure ecosystem (Azure OpenAI, Azure AI Foundry, Azure AI Search, Document Intelligence), engineering hybrid vector/keyword search, semantic ranking, and security trimming strategies.
• Enterprise Security & Responsible AI: Design authentication and access control schemes (Entra ID, OAuth 2.0, RBAC, Managed Identities) and build defenses against AI vulnerabilities (prompt injection, data leakage, OWASP Top 10 for LLMs) with robust PII protection.
• Technical Leadership & Collaboration: Author comprehensive architecture artifacts (C4 models, ADRs), drive technical roadmap discussions with US product partners, mentor engineering leads, and set organization-wide engineering standards.
   

Essential Skills & Experience

• Professional Experience: 12+ years in software engineering, including 4+ years as a Solution or Enterprise Architect, with 2+ years designing and running LLM-based applications in enterprise production.
• Primary Skill — Hands-on Databricks Mastery:3+ years of production experience designing and operating data pipelines on Databricks (preferably Azure Databricks).Deep practical implementation of Medallion architecture (Bronze/Silver/Gold) and data evolution patterns.Expert-level Apache Spark (PySpark, Spark SQL, or Scala) performance optimization (partitioning, file sizing, cluster sizing, cost governance).Delta Lake mastery (ACID transactions, schema enforcement/evolution, MERGE operations, change data feed, time travel).Ingestion and orchestration depth using Auto Loader, Structured Streaming, Delta Live Tables/Lakeflow, and Databricks Workflows.Unified governance implementation via Unity Catalog (lineage, access control, classification).
• Mandatory Skill — Model Context Protocol (MCP): Hands-on experience building and deploying MCP servers and clients (e.g., using FastMCP or official SDKs), tool schemas, stdio and streamable HTTP transports, and agent platform integrations (Azure AI Foundry).
• Microsoft Azure & AI Ecosystem: Comprehensive experience across Azure AI Search, Azure OpenAI, Azure AI Foundry, Container Apps, Service Bus, Cosmos DB, and Key Vault.
• Agentic Frameworks & Production RAG: Demonstrated success deploying production RAG architectures and agentic workflows using LangChain, LangGraph, or Semantic Kernel.
• System Design, Debugging & Code: Polyglot engineering skills in Python, TypeScript, or Java; proven ability to trace and debug distributed issues across asynchronous queues, databases, and model endpoints; hands-on CI/CD and IaC (Terraform, Bicep) proficiency.
• Communication: Exceptional verbal and written English communication skills to lead technical debates, justify trade-offs, and align roadmaps with US-based peers and executives.
   

Bonus Points For:

• Practical experience operationalizing Databricks Mosaic AI Vector Search, Model Serving, and MLflow.
• Workflow orchestration experience with tools such as n8n, Azure Logic Apps, or Microsoft Copilot Studio.
• Exposure to multi-cloud AI platforms including Google Cloud Vertex AI or Gemini.
• Implementation experience with LLM evaluation and observability stacks (e.g., Langfuse, Arize Phoenix).
• Industry credentials: Azure Solutions Architect Expert, Azure AI Engineer Associate, or Databricks Certified Solutions Architect / Data Engineer

Key Skills

Education

Any Graduate