Job Title: AI Engineer Consultant
Location: Hyderabad
Experience: 5-7 years
Role Overview
We are hiring a hands-on AI Engineer to develop end-to-end design of AI-enabled, cloud-native systems on Azure — owning everything from agentic workflow design through to microservices, deployment, and production delivery.
What You Will Build
- Agentic workflows and multi-agent systems using LangGraph on Azure
- AI-enabled microservices and REST APIs integrating LLMs, RAG pipelines, and tool-use
- End-to-end GenAI applications — from data ingestion and embedding to agent orchestration and UI
- Cloud-native systems on Azure — containerised, scalable, production-observable
- RAG pipelines: chunking, embedding, vector search, reranking, and eval
- Integrations with enterprise data sources, APIs, and Azure AI and Cognitive Services
Must-Have Technical Skills
- LangGraph — stateful agent graphs, multi-step reasoning, tool-calling, memory, human-in-the-loop
- Azure AI Foundry — agent deployment, prompt flow, model management, Azure OpenAI Service
- GenAI / LLMs — GPT-4o, open-source models; prompt engineering, context management, eval
- RAG — end-to-end pipeline design: ingestion, chunking, embedding, hybrid retrieval, reranking
- Vector databases — Azure AI Search, CosmosDB, Chroma, or Pinecone
- Azure cloud-native — AKS, Azure Container Apps, Azure Functions, Docker, CI/CD
- MCP (Model Context Protocol) for agent interoperability
Good to Have
- Semantic Kernel or AutoGen for additional multi-agent patterns
- Open-source LLM deployment — Ollama, vLLM, or HuggingFace inference
- Fine-tuning / LoRA / PEFT for domain-specific model adaptation
- React or lightweight frontend — for building AI application interfaces
- Azure AI Engineer Associate certification or equivalent
What We Expect
- 5-7 years in software engineering; 3+ years hands-on in AI/ML and GenAI — not just exposure
- Shipped at least one agentic or RAG system to production, end-to-end
- Comfortable working directly with clients and cross-functional teams in a consulting environment
Required Skills
API Gateway DevOps GitHub Actions Python Applications Development Framework Azure
