Job Title: GenAI Architect
Location: Hyderabad
Experience: 10–15 years (with 2–5+ years in AI/ML and recent GenAI exposure)
Role Overview
We are seeking a highly experienced GenAI Architect to lead the design and implementation of next-generation AI-powered systems. This role will drive architecture, platform strategy, and enterprise adoption of Generative AI solutions across business domains.
You will work closely with engineering, product, and business stakeholders to build scalable, secure, and production-grade AI systems leveraging LLMs, agents, and modern AI ecosystems.
What You Will Build
- Enterprise Agents and related agentic workflows on OCI and Azure AI Foundry
- RAG pipelines — ingestion, chunking, embedding, hybrid retrieval, reranking
- Multi-agent orchestration using LangGraph (stateful graphs, tool use, memory)
- Vector search integrations: Oracle 23ai, pgvector, Chroma, or Pinecone
- LLM integration across Azure OpenAI, open-source models (Ollama / vLLM), and OCI AI services
Must-Have Technical Skills
- LangGraph stateful agent graphs, multi-step reasoning, tool-calling, human-in-the-loop
- RAG architecture — end-to-end: chunking strategies, embedding models, reranking, eval
- Vector databases — hands-on with at least two (Oracle 23ai, pgvector, Chroma, Pinecone, Weaviate)
- Azure AI Foundry — agent deployment, model management, prompt flow
- OCI AI Services — OCI Data Science, Oracle 23ai vector search, Generative AI Service
- Open-source LLMs — deployment and inference with Ollama, vLLM, or HuggingFace
- Python — strong; async, API design, prompt engineering, eval scripting
- Docker / Kubernetes — containerised AI workload deployment
Good to Have
- Semantic Kernel or AutoGen for multi-agent patterns
- Fine-tuning / LoRA / PEFT for domain adaptation
- MCP (Model Context Protocol) for agent interoperability
- Knowledge graphs for enterprise AI
- Azure AI Engineer or OCI AI Foundations certification
What We Expect
- 10–15+ years in software / solutions engineering; 4+ years hands-on in AI/ML and GenAI
- Delivered at least one RAG or agentic system to production — not just a POC
- Comfortable owning end-to-end: architecture → code → deployment → production handover
- Able to mentor engineers and set technical standards for the team
Required Skills
API Gateway Azure DevOps GitHub Actions Applications Development Framework Python
