Job Description

We are seeking a highly skilled Agentic AI Developer with 5+ years of experience in building, deploying, and scaling AI-powered applications. The ideal candidate should have strong expertise in LLMs, multi-agent frameworks, orchestration tools, and cloud-based AI solutions, with a proven track record of developing production-grade intelligent agents.

Key Responsibilities

• Design, develop, and deploy agentic AI applications leveraging LLMs (OpenAI, Anthropic, Llama, Mistral, etc.).

• Build and orchestrate multi-agent systems for automation, reasoning, and decision-making.

• Work with frameworks and libraries like LangChain, LlamaIndex, Semantic Kernel, CrewAI, AutoGen, etc.

• Develop APIs, connectors, and integrations with third-party services and enterprise tools.

• Optimize LLM applications for performance, cost efficiency, and scalability.

• Implement RAG (Retrieval-Augmented Generation) pipelines and knowledge graphs.

• Ensure data privacy, security, and compliance in AI solutions.

• Collaborate with product, data science, and engineering teams in an Agile environment.

• Stay updated with advancements in Generative AI, agentic architectures, and AI research.

Required Skills & Experience

• 5+ years of experience in AI/ML, NLP, or full-stack AI development.

• Hands-on expertise with LLM APIs (OpenAI, Anthropic, Cohere, Google Vertex AI, Azure OpenAI).

• Strong experience with LangChain, LlamaIndex, Semantic Kernel, CrewAI, AutoGen or similar frameworks.

• Proficiency in Python, FastAPI, Flask, or Node.js for backend/API development.

• Experience with vector databases (Pinecone, Weaviate, Milvus, FAISS).

• Knowledge of RAG, fine-tuning, embeddings, and prompt engineering.

• Strong skills in cloud platforms (AWS, Azure, GCP) for AI deployment.

• Familiarity with CI/CD, Docker, Kubernetes for scalable AI services.

• Solid understanding of data pipelines, APIs, and microservices architecture.

Good to Have

• Experience with knowledge graphs, reasoning engines, or symbolic AI.

• Exposure to Reinforcement Learning (RLHF/RLAIF).

• Background in MLOps and AI model lifecycle management.

• Research or open-source contributions in Generative AI / multi-agent systems.

• Familiarity with frontend frameworks (React, Next.js) for AI-driven applications.

Skills Required

• AgenticAI • LLMs • LangChain • LlamaIndex • SemanticKernel • CrewAI • AutoGen • Python • FastAPI • Flask • Node.js • APIs • RAG • Embeddings • FineTuning • PromptEngineering • VectorDB • Pinecone • Weaviate • Milvus • FAISS • AWS • Azure • GCP • Docker • Kubernetes • Microservices • MLOps • KnowledgeGraphs • RLHF • RLAIF • React • Next.js • CI/CD • DataPipelines