Job Summary :

We are looking for a hands-on AI Architect with strong expertise in Generative AI, LLMs, RAG, and Agentic AI to design and deliver scalable, secure, production-grade enterprise AI solutions.

Key Responsibilities :

- Design end-to-end GenAI, LLM, RAG, and Agentic AI architectures.

- Design and implement Multi-Agent systems, agent orchestration, tool calling, memory, and workflows.

- Architect scalable RAG pipelines, including embeddings, vector search, hybrid search, re-ranking, and retrieval optimization.

- Define architecture decisions considering scalability, performance, security, latency, and cost.

- Integrate LLM solutions with enterprise applications, APIs, databases, and microservices.

- Lead AI solution design across Azure / GCP.

- Implement MLOps/LLMOps, CI/CD, monitoring, observability, and AI governance.

- Provide technical leadership, architecture reviews, mentoring, and client-facing solutioning.

Required Skills :

- 10+ years of software engineering experience with 4+ years in AI/ML/GenAI.

- Strong hands-on experience in GenAI, LLMs, RAG, and Agentic AI.

- Strong proficiency in Python and experience with FastAPI / REST APIs / Microservices.

- Experience with LangChain / LangGraph / LlamaIndex / Semantic Kernel or equivalent.

- Experience with OpenAI / Azure OpenAI / Claude / Gemini / LLaMA or equivalent LLMs.

- Strong knowledge of Vector Databases - Pinecone, FAISS, Milvus, Chroma, Azure AI Search, etc.

- Experience with Docker, Kubernetes, distributed systems, API orchestration, and asynchronous workflows.

- Experience with Azure / GCP.

- Strong understanding of AI security, governance, responsible AI, and LLM observability.