Principal genai engineer – backend / fullstack

8-14 years of experience in software engineering (backend or fullstack) 2+ years of hands-on experience with LLMs (RAG, agents, prompt engineering) Strong experience building production-grade distributed systems Proficiency in Python Strong experience with SQL & No SQL databases Hands-on experience with Lang Chain, Lang Graph, or similar frameworks Experience deploying systems on AWS / Azure / GCP Strong understanding of APIs, microservices, and system design Experience with vector databases (Pinecone, Weaviate, FAISS, etc.) Familiarity with CI/CD pipelines and Dev Ops practices Roles &

Develop and optimize LLM-based solutions: Lead the design and deployment of large language models, leveraging techniques like prompt engineering, retrieval-augmented generation (RAG), and agent-based architectures. Codebase ownership: Build and maintain/review high-quality, efficient code in Python (using frameworks like Lang Chain/Lang Graph) and SQL, focusing on reusable components, scalability, and performance best practices. Cloud integration: Aide in deployment of Gen AI applications on cloud platforms (Azure, GCP, or AWS), optimizing resource usage and ensuring robust CI/CD processes. Cross-functional collaboration: Work closely with product owners, data scientists, and business SMEs to define project

, translate technical details, and deliver impactful AI products. Mentoring and guidance: Provide technical leadership and knowledge-sharing to the engineering team, fostering best practices in machine learning and large language model development.

Exposure to frontend frameworks (React, Next.js) for fullstack roles Understanding of model evaluation, fine-tuning, or LLMOps Experience building multi-tenant or enterprise Saa S platforms