Job Title: Lead GenAI Engineer – Generative AI, Agentic AI & Azure

Location: Hybrid - Bengaluru

Employment : Full Time With VDart Digital

Joining Preference: Immediate Joiners / Short Notice Preferred

Role Overview

- We are seeking an experienced GenAI Lead Engineer with strong hands-on expertise in Python, Generative AI, Agentic AI, and Microsoft Azure to lead the technical design and delivery of enterprise-grade AI solutions.
- The ideal candidate will combine deep software engineering capabilities with expertise in LLM architectures, multi-agent systems, RAG pipelines, and Azure AI services. This role involves driving technical decisions, establishing engineering best practices, mentoring engineers, and delivering scalable, secure, and production-ready AI applications.
- The candidate should be capable of translating business objectives into robust technical solutions while remaining hands-on with architecture, development, integration, and deployment.

Key Responsibilities

- Lead the design, architecture, development, and deployment of Generative AI and Agentic AI applications using Python and Azure AI services.
- Design and implement agentic workflows involving planning, reasoning, tool calling, multi-agent collaboration, and autonomous task execution.
- Architect scalable LLM-based solutions using RAG, embeddings, semantic search, vector databases, and enterprise knowledge retrieval.
- Drive technical implementation using Azure OpenAI, Azure AI Foundry, Azure AI Search, and other relevant Azure services.
- Develop and review production-grade Python applications, backend services, APIs, and reusable AI components.
- Establish best practices for prompt engineering, context management, model selection, agent orchestration, and response grounding.




- Lead the implementation of AI orchestration frameworks such as LangGraph, LangChain, Semantic Kernel, CrewAI, or AutoGen.
- Design enterprise integrations connecting AI agents with APIs, databases, business applications, and external tools.
- Define strategies for LLM evaluation, agent testing, hallucination mitigation, observability, latency optimization, and cost management.
- Ensure AI solutions follow security, privacy, governance, responsible AI, and enterprise compliance requirements.
- Lead code reviews, technical design discussions, engineering standards, and troubleshooting of complex production issues.
- Mentor and guide engineers, collaborate with architects and stakeholders, and drive technical delivery across the AI development lifecycle.
- Work with DevOps, cloud, security, and platform teams to establish reliable CI/CD pipelines and production deployment practices.

Required Skills and Experience

- 8 to 12 years of software engineering experience
- Demonstrated experience designing and delivering production-grade Generative AI applications.
- Strong hands-on expertise in Agentic AI, agent orchestration, tool calling, and multi-step or multi-agent workflows.
- Deep understanding of LLM architectures, RAG, embeddings, vector search, prompt engineering, and context management.
- Robust practical experience with Microsoft Azure AI services, particularly Azure OpenAI,



Azure AI Foundry, and Azure AI Search or equivalent Azure AI capabilities.
- Experience architecting and developing scalable Python-based applications, APIs, and microservices using FastAPI, Flask, or similar frameworks.
- Hands-on experience with LangGraph, LangChain, Semantic Kernel, CrewAI, AutoGen, or comparable agent frameworks.
- Experience designing enterprise-grade AI integrations with APIs, databases, document repositories, and business systems.
- Strong understanding of LLM evaluation, agent reliability, hallucination mitigation, security guardrails, and production observability.
- Experience with application architecture, code reviews, automated testing, CI/CD, Docker, and cloud deployment.
- Ability to make technical decisions, solve complex engineering challenges, and translate business requirements into practical AI solutions.
- Strong communication, stakeholder management, technical leadership, and mentoring capabilities.

Preferred Skills

- Experience designing secure, scalable AI solutions using Azure Functions, Azure Container Apps, AKS, or other Azure hosting services.
- Knowledge of Azure identity and security capabilities, including Microsoft Entra ID, managed identities, Key Vault, and role-based access control.
- Experience with AI tracing, monitoring, evaluation frameworks, and production performance optimization.
- Familiarity with enterprise AI governance, responsible AI practices, data privacy, and access-controlled retrieval.
- Experience establishing reusable AI engineering frameworks, reference architectures, and development standards.
- Exposure to MLOps, LLMOps, infrastructure automation, and enterprise-scale AI platform integration.

📌 Lead GenAI Engineer (Bengaluru)
🏢 VDart Digital
📍 Bengaluru