Full-Stack AI Engineer

About the Role:

Full-Stack AI Engineer

Key Responsibilities:

• Design, implement, and optimize

  RAG pipelines

  for AI-driven applications.
• Build and manage

  vector database solutions

  (e.g., Pinecone, Weaviate, Qdrant, FAISS).
• Develop

  semantic search and information retrieval systems

  .
• Implement

  production-grade ML systems

  , ensuring scalability, reliability, and performance.
• Collaborate with product and research teams to integrate

  LLM-based solutions

  .
• Apply

  prompt engineering

  techniques for improved LLM outputs.
• Optimize

  document chunking strategies

  for knowledge ingestion pipelines.
• Work on

  caching, performance tuning, and infrastructure optimization

  (e.g., Redis).

Core Skills:

• RAG implementation

• Vector database expertise

• Semantic search optimization

• Production ML systems deployment

Technical Requirements:

• Proficiency with

  LangChain / LlamaIndex

  frameworks
• Hands-on experience with

  vector DBs

  : Pinecone, Weaviate, Qdrant, FAISS
• Strong understanding of

  LLMs

  : OpenAI, Sentence Transformers
• Expertise in

  Python

  (with NumPy and supporting libraries)
• Knowledge of

  prompt engineering techniques

• Experience with

  document chunking strategies

• Familiarity with

  Redis/caching mechanisms

Preferred Qualifications:

• 3+ years of experience in AI/ML engineering
• Proven track record of deploying

  AI solutions in production environments

• Strong problem-solving skills and ability to work in fast-paced environments
• Experience collaborating with cross-functional teams (engineering, research, product)

Why Join Us?

• Opportunity to work on cutting-edge AI products with real-world impact
• Collaborative team culture focused on innovation and scalability
• Growth opportunities in a rapidly evolving AI ecosystem