GenAI Full-Stack Developer

Job Summary:

We are seeking a highly skilled GenAI Full-Stack Developer with strong expertise in Python, LangChain, LangGraph, Vector Databases, and Agentic AI frameworks. The ideal candidate will design, develop, and deploy scalable AI-driven applications, intelligent agents, and automation workflows that leverage LLMs, retrieval-augmented generation (RAG), embeddings, and modern full-stack technologies.

This role requires hands-on engineering skills, architectural thinking, and the ability to lead end-to-end GenAI project delivery.

Key Responsibilities

GenAI / LLM Engineering

• Build and deploy Generative AI applications using LangChain, LangGraph, and Python-based agentic frameworks.
• Develop RAG (Retrieval-Augmented Generation) pipelines using embeddings, vector stores, and LLM orchestration.
• Implement Agentic AI workflows including multi-agent systems, tool-calling, memory, and reasoning chains.
• Fine-tune, evaluate, and optimize LLM models for performance, accuracy, and cost.
• Integrate third-party LLMs (OpenAI, Anthropic, Azure, HuggingFace, etc.).

Backend Development (Python)

• Design and maintain backend services using Python, FastAPI, Flask, or Django.
• Build scalable microservices integrating GenAI capabilities.
• Implement robust API layers to expose AI functionalities securely and reliably.

Vector Database & Knowledge Systems

• Work with vector databases such as Pinecone, Chroma, Weaviate, Milvus, or similar.
• Design embedding pipelines, indexing strategies, and semantic search systems.
• Implement retrieval layers for LLMs to enhance context-aware responses.

Frontend Development

• Develop interactive UIs for GenAI apps using React, Next.js, or equivalent front-end frameworks.
• Collaborate with UX designers to create intuitive user experiences for AI-powered interfaces.

Architecture & DevOps

• Design modular, scalable AI system architectures.
• Deploy applications on Cloud Platforms (AWS, GCP, Azure).
• Implement CI/CD pipelines for model deployment and application integration.
• Monitor system performance and optimize compute and storage costs.

Collaboration & Leadership

• Work cross-functionally with data scientists, business analysts, product owners, and ML engineers.
• Lead technical discussions and guide junior developers on GenAI best practices.
• Translate business needs into scalable technical solutions.

Required Skills & Qualifications

• Bachelor’s or Master’s degree in Computer Science, Engineering, or related field.
• 5 years of software development experience, with strong expertise in Python.
• Hands-on experience with LangChain and LangGraph.
• Strong knowledge of LLMs, embeddings, vector search, RAG pipelines.
• Experience building Agentic AI systems (tool calling, planners, agents, memory frameworks).
• Strong backend and API development experience.
• Experience with React/Next.js or similar for frontend development.
• Familiarity with cloud services (AWS/GCP/Azure).
• Understanding of security, testing, and performance optimization.

Preferred Qualifications

• Experience with OpenAI GPT-4/5, Claude, Llama, or open-source LLMs.
• Knowledge of ML Ops, model evaluation, and prompt engineering.
• Exposure to containerization using Docker and Kubernetes.
• Experience integrating databases (SQL/NoSQL) with vector stores.
• Experience working in agile teams.