Gen AI Developer

• Work on end-to-end design and development of

  Generative AI applications

  using LLMs.


• mplement

  RAG pipelines

  using embeddings, hybrid search, semantic indexing, and reranking.


• Design and optimize

  Vector DB structures

  (FAISS, Qdrant, Pinecone, Weaviate, Chroma) for high-performance retrieval.


• Create

  knowledge ingestion pipelines

  including chunking, preprocessing, OCR and document embedding strategies.


• Build scalable backend services using

  Python / FastAPI / Node

  integrated with LLMs (OpenAI, Anthropic, Gemini, Llama).


• Own POCs, architecture decisions, prompt engineering frameworks, and performance tuning.


• Drive experimentation of LLM models, fine-tuning, LoRA, embedding selection and evaluation metrics.


• Collaborate with cloud and product teams to deploy scalable GenAI solutions on AWS / GCP / Azure.


• Stay current with research trends in GenAI, multi-agent systems and knowledge reasoning.

Required Skills & Expertise

• 2 5 years overall development experience,

  1+ years in Generative AI

  .


• Strong expertise in

  LangChain & LangGraph

  for orchestration, agents, tools and memory management.


• Hands-on experience with

  Vector Databases

  (Qdrant / Pinecone / FAISS / Chroma / Weaviate).


• Deep understanding of

  LLM architecture

  , embeddings, RAG, token optimization & context strategies.


• Experience with

  Multi-Agent Frameworks

  (Planner, Worker, Verifier, Summarizer).


• Strong programming experience in

  Python (preferred)

  or NodeJS.


• Familiarity with

  LLM model providers

  OpenAI, Anthropic, Gemini, HuggingFace, Meta Llama.


• Experience with cloud-native deployment

  Docker, Kubernetes, CI/CD

  .


• Understanding of prompt engineering, safety guardrails, hallucination prevention & evaluation.


• Ability to conduct research, run experiments and deliver production-ready systems.