Generative AI/LLM Application Developer

Description :

Role : GenAI / LLM Application Developer (Python, LangChain, LangGraph, MCP)

They are seeking an experienced AI Developer with strong expertise in Python, LangChain, LangGraph, and Model Context Protocol (MCP) to design and build intelligent AI-powered applications.

The ideal candidate will work on developing LLM-powered workflows, AI agents, and automation solutions that integrate with enterprise systems, APIs, and data platforms.

This role requires hands-on experience building AI agents, orchestrating LLM workflows, and integrating AI models into production-grade applications.

Key Responsibilities :

- Design and develop AI-powered applications using Python and modern LLM frameworks.

- Build LLM workflows using LangChain and LangGraph.

- Implement AI agents and multi-agent systems for enterprise use cases.

- Integrate LLM models (OpenAI, Anthropic, or open-source models) into applications.

- Use Model Context Protocol (MCP) to connect LLMs with enterprise tools and services.

- Develop prompt engineering strategies and structured output pipelines.

- Build RAG (Retrieval-Augmented Generation) pipelines using vector databases.

- Integrate AI systems with APIs, databases, and enterprise platforms.

- Implement evaluation, monitoring, and guardrails for AI systems.

- Collaborate with product teams and architects to design scalable AI solutions.

- Optimize performance and cost for LLM inference workloads.

Required Skills & Qualifications :

- 4 to 7+ years of software development experience.

- Strong programming skills in Python.

- Hands-on experience with LangChain for building LLM applications.

- Experience using LangGraph for agent orchestration and workflow management.

- Knowledge of Model Context Protocol (MCP) for integrating tools with AI agents.

- Experience integrating LLMs such as OpenAI GPT, Claude, Llama, or similar models.

- Experience with REST APIs and microservices development.

- Familiarity with vector databases (Pinecone, Weviate, Chroma, or FAISS).

- Strong understanding of prompt engineering and LLM architecture.

Preferred Skills :

- Experience building AI agents and autonomous workflows.

- Knowledge of RAG pipelines and document processing systems.

- Familiarity with Docker and cloud environments (AWS, Azure, or GCP).

Nice to Have :

- Experience with multi-agent frameworks.

- Knowledge of AI safety, guardrails, and prompt security.

- Familiarity with transformers and HuggingFace ecosystem.

- Experience with streaming AI applications or chat-based systems.