Full Stack AI Engineer

GraaS is looking for passionate & curious AI Engineer. As part of our AI team, you will design & implement improvements to the backbone of our core architecture. The architecture is powered by knowledge graphs that capture information from unusual and myriad sources. Unlike traditional RAG systems that treat knowledge as a flat collection of documents, we’re building rich, hierarchical representations that mirror how human experts think, reason & comprehend.

What you’ll do:

  • Graph Architecture & Design: design scalable knowledge graph architectures, develop novel embeddings to capture nuanced relationships, and build efficient indexing and retrieval for real-time querying.
  • Evals for the Mind: defining the core components of the human mind, building strong mind architectures, giving customers confidence their minds improve over time, and advancing tone and style transfer to better reflect individuality.
  • RAG System Innovation: build next-generation RAG systems that merge graph-based reasoning with neural retrieval and include robust evaluation frameworks to optimize quality across query types.
  • Infrastructure & Scaling: scale infrastructure to support distributed, low-latency graph operations across thousands of instances with comprehensive monitoring and debugging tools.


What you’ll bring:

  • LLM Expertise & Application: deep understanding of how LLMs work with proven ability to apply them effectively, push their performance, and optimize through advanced prompt engineering techniques.
  • Python Performance Mastery: strong experience with Python beyond surface level, expert with asynchronous programming, event loop optimization, and performance tuning for high-scale applications.
  • RAG & Context Engineering: hands-on experience with retrieval-augmented generation, context engineering, and evaluation frameworks for LLM performance optimization.
  • ML Engineering Bridge: skilled traditional software engineer with deep familiarity in ML/AI systems—you understand both the engineering and AI sides without needing a research background.
  • Systems & Product Focus: ability to architect scalable backend systems while building AI-powered features that directly impact user experience and product outcomes.

Salary and Equity:

At GraaS, we take a market-based approach to compensation. Final offers are based on job-related skills, experience, location, and internal equity. Base salary is just one part of our total rewards package, including stock options and the opportunity to share in the company’s growth. The starting base salary range for this role in Bengaluru: Rs. 35 Lpa – Rs. 60 Lpa

How to apply:

If you’re excited about this role but your past experience doesn’t align perfectly with every qualification in the job description, we encourage you to apply anyway. You may be just the right candidate for this or other roles. Send in your resume to [email protected]