Lead Agentic AI Engineer

We are looking for a Lead Agentic AI Engineer to lead the design, development, and delivery of scalable Generative AI and Agentic AI solutions for enterprise applications. The ideal candidate should have strong hands-on experience in LLMs, RAG, LangChain, LangGraph, and AI agents, along with strong backend engineering expertise in Python and Java.

We are looking for an engineer who can combine strong software engineering fundamentals with deep hands-on GenAI expertise and take ownership of AI systems from architecture through production deployment. If you have built and deployed production-grade Agentic AI/LLM applications and enjoy solving complex enterprise problems, we'd love to hear from you.

Responsibilities:

• Design and build production-grade AI Agents, Agentic AI applications, and LLM-powered solutions.
• Develop end-to-end RAG pipelines, including ingestion, chunking, embeddings, retrieval, reranking, and generation.
• Build multi-step AI workflows using LangChain and LangGraph.
• Implement tool/function calling, memory, planning, and agent orchestration.
• Integrate LLMs with enterprise APIs, databases, knowledge bases, and external tools.
• Build scalable backend systems and microservices using Java and Python.
• Develop and integrate REST APIs, with hands-on experience in Django and Java 8+.
• Work on concurrency, multithreading, API automation, testing, observability, and AI guardrails.
• Lead architecture discussions, mentor engineers, and establish AI engineering best practices.

Requirements:

• 8+ years of software engineering experience.
• Strong hands-on experience building Generative AI / Agentic AI applications in production.
• Expertise in LLMs, RAG, LangChain, and LangGraph.
• Strong programming skills in Python and Java.
• Strong knowledge of Java 8+, Java EE, concurrency, multithreading, and design patterns.
• Experience with vector databases, embeddings, retrieval architectures, and REST APIs.
• Experience building scalable microservices and enterprise applications.
• Hands-on experience with API testing and automation.

Good to Have:

• Multi-agent systems and advanced LangGraph workflows.
• AI tool/function calling, memory, planning, and orchestration.
• Experience with Pinecone, Weaviate, Milvus, Qdrant, or FAISS.
• Experience with OpenAI, Azure OpenAI, Anthropic, Gemini, or other foundation models.
• LLM evaluation, observability, prompt management, and AI security/guardrails.
• Django, JavaScript, HTML5 and CSS3