We are looking for an experienced Generative AI Solutions Architect to design and develop scalable, enterprise-grade AI solutions.

The ideal candidate should have strong expertise in Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI Agents and agentic AI architectures.

The candidate will be responsible for defining end-to-end GenAI solutions, building intelligent AI workflows and leveraging frameworks such as LangChain, LangGraph, LlamaIndex and AutoGen.

Strong hands-on Python development experience and expertise in Microsoft Azure AI Foundry are essential.

Key Responsibilities :

- Design and architect end-to-end Generative AI solutions leveraging LLMs and modern AI technologies.

- Develop and implement RAG-based applications, including document ingestion, chunking, embeddings, vector search and retrieval pipelines.

- Design and build AI Agents and multi-agent systems to automate complex business workflows.

- Develop intelligent AI orchestration workflows using LangChain, LangGraph, LlamaIndex and AutoGen.

- Leverage Azure AI Foundry to build, deploy, manage and monitor enterprise-grade AI applications and agents.

- Evaluate and integrate different LLMs based on business requirements, performance and scalability.

- Develop AI-powered applications and backend services using Python.

- Implement prompt engineering, context management and LLM optimization techniques to improve response quality.

- Define scalable, secure and reliable GenAI architectures aligned with enterprise requirements.

- Collaborate with business stakeholders, product teams and engineering teams to translate business requirements into technical solutions.

- Establish best practices for AI governance, responsible AI, security and performance monitoring.

- Provide technical leadership and guidance to development teams throughout the solution lifecycle.

Required Technical Skills & Qualifications :

- Strong experience in Generative AI and Large Language Models (LLMs).

- Hands-on experience designing and implementing Retrieval-Augmented Generation (RAG) solutions.

- Strong understanding of AI Agents, agentic AI workflows and multi-agent architectures.

- Hands-on experience with one or more of the following frameworks :

1. LangChain

2. LangGraph

3. LlamaIndex

4. AutoGen

- Strong programming experience in Python.

- Hands-on experience with Microsoft Azure AI Foundry.

- Understanding of LLM orchestration, prompt engineering, embeddings and vector databases.

- Experience integrating LLMs with enterprise applications, APIs and external data sources.

- Knowledge of deploying, scaling and monitoring AI-powered applications.

- Understanding of AI security, responsible AI practices and enterprise-grade solution architecture.