? Senior Cloud & Generative AI Technical Lead

Experience: 15+ Years

Primary Skills: Azure, Generative AI, LangChain, LangGraph, RAG, Vector Databases,

Secondary Skills: PostgreSQL, AWS, DevOps

Role Overview

We are looking for a highly experienced Senior Cloud & Generative AI Architect with 15+ years of overall technology experience and strong hands-on expertise across Microsoft Azure and AWS. The candidate will be responsible for architecting and delivering scalable, secure, cloud-native and AI-enabled enterprise solutions.

The ideal candidate should combine strong cloud architecture capabilities with hands-on Generative AI engineering experience, particularly in developing agentic AI solutions, RAG pipelines, LangChain/LangGraph-based workflows, LLM integrations, and enterprise AI platforms.

Key Responsibilities

- Design end-to-end enterprise solutions across Azure and AWS, covering application, integration, data, security, networking, observability, and deployment architecture.
- Define cloud-native and multi-cloud architecture patterns with focus on scalability, security, resilience, performance, and cost optimization.
- Architect and develop Generative AI and Agentic AI solutions using LangChain, LangGraph and leading foundation models.
- Design reusable Retrieval-Augmented Generation (RAG) pipelines, including document ingestion, parsing, chunking, metadata enrichment, embedding generation, vector indexing, retrieval, reranking and grounded response generation.
- Design and implement multi-agent and agentic workflows using LangGraph, including state management, tool calling, memory, human-in-the-loop workflows and agent-to-agent interactions.
- Integrate LLM applications with enterprise systems, APIs, databases,



document repositories and business applications.
- Design enterprise knowledge platforms leveraging vector databases/vector search and hybrid retrieval techniques.
- Implement AI application security controls including authentication, authorization, prompt-injection protection, data isolation, guardrails, PII handling and responsible AI practices.

Mandatory Skills:

- Solid knowledge across services in Azure such as:
- Azure OpenAI / Azure AI Foundry
- Azure AI Search
- Azure Container Apps / AKS / App Service / Functions
- Azure Storage / ADLS
- Azure SQL / Cosmos DB
- Microsoft Entra ID
- Azure Key Vault
- API Management
- Service Bus / Event Grid
- Application Insights / Azure Monitor

- Good exposure to Langchain/Langgraph. Hands-on experience designing stateful agent workflows, tool-calling agents and multi-step orchestration.
- Strong hands-on Python development experience, particularly for AI/ML applications.
- Knowledge about AI observability (Langfuse, Langsmith). Application/LLM tracing, logging, metrics, token monitoring and performance analysis.
- Strong experience designing and implementing production-grade RAG pipelines
- Experience with vector databases/search platforms such as Azure AI Search, Amazon OpenSearch, pgvector, Databricks Vector Search or equivalent
- Knowledge on OAuth/OIDC, Entra ID, AWS IAM, RBAC, secrets management and enterprise AI security

Good-to-Have Skills:

- PostgreSQL and advanced SQL knowledge
- Redis/caching technologies
- Good knowledge on AWS services like: S3, lamda, Step functions, Agent core, ECS/EKS, RDS/Aurora, AWS Cognito.
- MCP (Model Context Protocol)
- Kubernetes
- Terraform
- Multi-tenant SaaS architecture
- FinOps and LLM cost optimization

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🏢 Happiest Minds Technologies
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