Staff Backend Engineer

Responsibilities:
Backend Integration of LLM Architectures: Lead the development and maintenance of the backend infrastructure that powers state-of-the-art Large Language Model (LLM) architectures, including RAG, ReAct, and Agent-based systems. Architect data pipelines for processing extensive datasets and devise AI-powered endpoints crucial for our SaaS application and VSCode Extension.
Graph-Based Data Structure Design: Design and develop large-scale graph-based data structures that effectively model complex data stores. Create intricate, efficient structures that can be fed to our AI applications as context, ensuring both scalability and performance.
Intelligent SQL Ecosystem: Lead the design and development of a comprehensive SQL intelligence system encompassing query optimization, dynamic pipeline generation, and data lineage tracking. Leverage expertise in SQL query profiling, AST analysis, and parsing to create a sophisticated engine focused on query performance improvements and implementing granular column-level lineage.
Impact:
Innovation at the Forefront: Push the boundaries of software engineering by combining traditional techniques with cutting-edge AI technologies.
High Visibility and Impact: Directly affect the productivity and capabilities of global data teams, as your contributions will be crucial to the daily operations of thousands of users spread across 100s of countries.
Open Source Contribution: As part of our commitment to the developer community, you will contribute to our open-source initiatives, gaining recognition in the tech community.
Career Growth: This role is a launchpad into the rapidly advancing field of AI, offering exposure to state-of-the-art technologies and generative AI applications.
Requirements:
10+ years of experience building Python-based web application backends and the infrastructure on which they run.
Extensive experience in building scalable back-end systems, APIs, and microservices.
Deep understanding of cloud platforms (AWS, Azure, GCP) and containerization technologies (Docker, Kubernetes).
Preferred:
Experience with FastAPI for building high-performance APIs.
Familiarity with AI and machine learning concepts, particularly in the context of Large Language Models (LLMs).
Strong proficiency in SQL, including query profiling, optimization, and performance tuning.
Experience with SQL Abstract Syntax Tree (AST) analysis and working with SQL parsers (e. g., sqlglot).

Experience
8-12 yrs