TECHNICAL LEAD - Gen AI

Happiest Minds Technologies; Bengaluru; On-site; INR 400,000 - 700,000; Full time

Job summary

Happiest Minds Technologies seeks a GenAI Engineer with 10+ years in software engineering and AI to design, build, and deploy enterprise-grade Generative AI and Agentic AI solutions on Azure. You will architect multi-agent systems, MCP-based integrations, and scalable AI workflows to automate business processes.

Lead the integration of LLMs with enterprise systems, ensure observability, and drive performance enhancements across tool calling, RAG, and semantic search initiatives.

Qualifications

• Experience leading design and deployment of Generative and Agentic AI in enterprise settings.
• Hands-on with MCP servers/clients and MCP-based integrations.
• Proven ability to build AI agents for business process automation and productivity.

Responsibilities

• Design, develop, and deploy enterprise-grade Generative AI and Agentic AI solutions.
• Build AI agents for business process automation, knowledge management, project management, and enterprise productivity.
• Develop and integrate AI agents using Agentic AI frameworks, multi-agent architectures, and orchestration platforms.
• Design and implement MCP servers, MCP clients, and MCP-based enterprise integrations.
• Develop Agent-to-Agent communication mechanisms for collaboration between distributed AI agents.
• Implement Agent Discovery frameworks for dynamic identification, registration, capability mapping, and invocation of AI agents.
• Design secure Sandbox environments for tool execution, code execution, validation, and controlled agent operations.
• Develop custom tools, plugins, workflows, and agent capabilities within enterprise AI frameworks.
• Integrate LLMs with enterprise systems, APIs, databases, and knowledge repositories.
• Design Retrieval-Augmented Generation architectures using vector databases and semantic search technologies.
• Build intelligent workflows involving tool calling, function calling, planning, reasoning, and autonomous execution.
• Deploy AI solutions on Azure cloud infrastructure and enterprise environments.
• Implement observability, tracing, monitoring, and evaluation frameworks for AI applications.
• Optimize AI agent performance, response quality, scalability, and operational efficiency.
• Collaborate with business stakeholders and technical teams to define AI strategy and implementation roadmaps.

Skills

Agentic AI

Multi-Agent Systems

MCP

A2A

Agent Discovery

AI Sandboxing

LLM Orchestration

Tool Calling

Prompt Engineering

RAG

Semantic Search

Observability

LangGraph

LangChain

OpenAI

Azure OpenAI

Python

FastAPI

REST APIs

Microservices

Tools

LangChain

PGVector

Azure OpenAI

Langfuse

Azure Monitor

Job description

Experience: 10+ Years in Software Engineering, AI/ML, Generative AI, Agentic AI, Enterprise Automation, Cloud Architecture, and Azure-based Solutions.

Core Responsibilities

GenAI Engineer

Experience: 10+ Years in Software Engineering, AI/ML, Generative AI, Agentic AI, Enterprise Automation, Cloud Architecture, and Azure-based Solutions.

Core Responsibilities

• Design, develop, and deploy enterprise-grade Generative AI and Agentic AI solutions.
• Build AI agents for business process automation, knowledge management, project management, and enterprise productivity.
• Develop and integrate AI agents using Agentic AI frameworks, multi-agent architectures, and orchestration platforms.
• Design and implement Model Context Protocol (MCP) servers, MCP clients, and MCP-based enterprise integrations.
• Develop Agent-to-Agent (A2A) communication mechanisms for collaboration between distributed AI agents.
• Implement Agent Discovery frameworks for dynamic identification, registration, capability mapping, and invocation of AI agents.
• Design secure Sandbox environments for tool execution, code execution, validation, and controlled agent operations.
• Develop custom tools, plugins, workflows, and agent capabilities within enterprise AI frameworks.
• Integrate Large Language Models (LLMs) with enterprise systems, APIs, databases, and knowledge repositories.
• Design Retrieval-Augmented Generation (RAG) architectures using vector databases and semantic search technologies.
• Build intelligent workflows involving tool calling, function calling, planning, reasoning, and autonomous execution.
• Deploy AI solutions on Azure cloud infrastructure and enterprise environments.
• Implement observability, tracing, monitoring, and evaluation frameworks for AI applications.
• Optimize AI agent performance, response quality, scalability, and operational efficiency.
• Collaborate with business stakeholders and technical teams to define AI strategy and implementation roadmaps.

Technical Skills - Experience atleast 4 yearsGenerative AI & Agentic AI

• Agentic AI Architecture
• Multi-Agent Systems
• MCP (Model Context Protocol)
• A2A (Agent-to-Agent Communication)
• Agent Discovery
• AI Sandboxing
• LLM Orchestration
• Tool Calling & Function Calling
• Prompt Engineering
• RAG
• Semantic Search
• AI Evaluation & Observability
• LangGraph
• LangChain
• OpenAI
• Azure OpenAI

Cloud & DevOps - 4 years

• Microsoft Azure
• Azure Functions
• Azure Kubernetes Service (AKS)
• Azure Container Apps
• Azure App Services
• Azure DevOps
• CI/CD Pipelines

Backend Development - 5 years

• Python
• FastAPI
• REST APIs
• Microservices Architecture

Databases & Search - 5 years

• PostgreSQL
• PGVector
• Vector Databases
• Knowledge Graphs
• Enterprise Search

Monitoring & Observability -8 years

• Langfuse
• Application Insights
• Azure Monitor
• Logging & Tracing Frameworks

Shivanku Chauhan

GenAI Engineer Experience: 10+ Years in Software Engineering, AI/ML, Generative AI, Agentic AI, Enterprise Automation, Cloud Architecture, and Azure-based Solutions. Core Responsibilities ? Design,?