Full-Stack AI Engineer

Full-Stack AI Engineer

Key Responsibilities

• Design and implement

  RAG-based AI applications

  with optimized semantic search.
• Build and manage

  vector database solutions

  (Pinecone, Weaviate, Qdrant, FAISS).
• Develop and maintain

  production-ready ML systems

  ensuring performance and scalability.
• Apply

  prompt engineering techniques

  to fine-tune model interactions.
• Handle

  document chunking, embedding generation, and retrieval optimization

  .
• Integrate

  LangChain/LlamaIndex

  frameworks for orchestration.
• Implement

  caching strategies

  (Redis or similar) for efficiency.
• Collaborate with cross-functional teams to deliver end-to-end AI solutions.

Core Skills

• Strong experience in

  RAG implementation

  .
• Expertise in

  vector databases

  (Pinecone, Weaviate, Qdrant, FAISS).
• Proficiency in

  semantic search optimization

  .
• Hands-on knowledge of

  production ML system deployment

  .

Technical Requirements

• Proficient in

  LangChain, LlamaIndex

  .
• Experience with

  OpenAI APIs, Hugging Face, Sentence Transformers

  .
• Strong programming skills in

  Python, NumPy

  , and ML libraries.
• Familiarity with

  prompt engineering

  best practices.
• Knowledge of

  document chunking techniques

  for retrieval systems.
• Experience with

  Redis or other caching mechanisms

  .

Preferred Qualifications

• 3–6 years of experience in

  AI/ML engineering or full-stack development

  .
• Strong problem-solving and optimization skills.
• Experience working in

  fast-paced startup or product environments

  .
• Knowledge of

  cloud deployment (AWS, GCP, or Azure)

  is a plus.

Why Join Us?

• Work with cutting-edge

  Generative AI and Retrieval systems

  .
• Opportunity to contribute to

  high-impact AI products

  in production.
• Collaborative, growth-oriented, and innovative work culture.