Full Stack Engineer

We are looking for a skilled Full Stack Developer with strong Python expertise and hands-on experience in Generative AI (GenAI) technologies. You will be part of a dynamic team building intelligent, scalable applications that leverage Large Language Models (LLMs) and modern web frameworks to transform enterprise workflows.

• Application Development: Build and maintain full-stack web applications integrating GenAI capabilities.
• GenAI Integration: Work with APIs such as OpenAI, Azure OpenAI, Hugging Face, and Lang Chain to embed LLM-driven features.
• Frontend Development: Develop responsive and user-friendly interfaces using React, Angular, or Vue.
• Data Integration: Connect applications to SQL/No
  
  SQL databases and vector stores like Pinecone, FAISS, or Weaviate.
• Prompt Engineering: Collaborate with AI engineers to design effective prompts and implement RAG (Retrieval-Augmented Generation) flows.
• Testing & Deployment: Implement CI/CD pipelines, write unit and integration tests, and deploy applications to cloud platforms (AWS, Azure).
• Team
  
  Collaboration:
  
  Work closely with product managers, designers, and ML engineers to deliver high-impact AI solutions.

• Programming
  
  Languages:
  
  Strong proficiency in Python
• Frontend Frameworks: Experience with React, Angular (v8+), or Vue.js.
• Backend Frameworks: Hands-on with FastAPI, Flask, experience with RESTful APIs and microservices.
• GenAI Tools: Familiarity with LLM APIs (OpenAI, Azure OpenAI), Lang Chain, and vector databases.
• Databases:
  
  Experience with Postgre
  
  SQL, Mongo
  
  DB, Dynamo
  
  DB, and vector stores.
• Cloud & Dev Ops: Exposure to AWS, Azure, or GCP; containerization (Docker, Kubernetes); CI/CD tools.
• Version Control: Proficient in Git and collaborative development workflows.
• Problem Solving: Strong debugging and optimization skills.

• Experience with Lang Chain, Llama Index, or similar orchestration frameworks.
• Understanding of RAG architecture and embeddings.
• Exposure to NLP, ML pipelines, or model fine-tuning.
• Familiarity with enterprise SDLC processes.
• UI/UX sensitivity for building intuitive AI-powered interfaces.