Senior AI Developer

We are looking for an experienced Lead AI Engineer to lead the design and development of production-grade generative AI, LLM, RAG, and agentic AI solutions. The ideal candidate should have strong hands-on experience in Python, LLMs, RAG architecture, AI agents, LangChain/LangGraph, vector databases, cloud, and MLOps, along with the ability to design scalable AI systems and mentor engineering teams.
Responsibilities:
Design and develop scalable GenAI and LLM-powered applications for enterprise use cases.
Architect and implement advanced RAG pipelines, including document processing, embeddings, retrieval, re-ranking, and evaluation.
Build agentic AI and multi-agent systems using frameworks such as LangChain, LangGraph, AutoGen, or Semantic Kernel.
Integrate LLMs such as OpenAI, Azure OpenAI, Claude, Gemini, or open-source LLMs.
Develop AI services and microservices using Python and FastAPI.
Work with vector databases such as FAISS, Pinecone, Weaviate, Milvus, or Azure AI Search.
Implement prompt engineering, function/tool calling, structured outputs, memory, and agent orchestration.
Build and maintain LLM evaluation and monitoring frameworks to improve accuracy, relevance, safety, and reliability.
Deploy AI solutions on Azure/AWS/GCP using Docker and Kubernetes.
Establish and improve MLOps/LLMOps pipelines, CI/CD, model monitoring, and production deployment practices.
Work on AI security, responsible AI, guardrails, prompt injection prevention, and LLM safety.
Drive technical architecture, code reviews, engineering best practices, and system design.
Mentor engineers and provide technical leadership across AI initiatives.
Requirements:
8-12 years of software/AI engineering experience.
Strong Python programming.
Hands-on generative AI/LLM experience.
Strong RAG architecture and implementation experience.
Experience with Agentic AI / AI Agents / Multi-Agent Systems.
Good to have: LangChain / LangGraph or equivalent agent frameworks.
Experience with Vector Databases.
Nice to have: LLM APIs such as OpenAI / Azure OpenAI / Claude / Gemini.
Experience in FastAPI / REST APIs / Microservices, Docker, and Kubernetes.
Experience with at least one major cloud platform: Azure, AWS, or GCP.
Understanding of MLOps / LLMOps.
Strong knowledge of AI system architecture and scalability.
Good technical leadership and mentoring experience.
Good to have: LlamaIndex, AutoGen, Semantic Kernel, Hugging Face Transformers, PyTorch / TensorFlow, MLflow / Kubeflow, Terraform and CI/CD, LLM evaluation and observability tools, AI red teaming / AI security, OWASP LLM Top 10 / NIST AI RMF, Fine-tuning / LoRA / QLoRA.
Knowledge graphs and hybrid search.

Experience
8-12 yrs