About the job
DiligenceSquared is in search of a pioneering Backend Engineer to join our team as we revolutionize the landscape of market due diligence through cutting-edge AI technology. In this foundational role, you will be instrumental in designing the architecture for our AI-driven engine, which coordinates autonomous research agents and voice AI systems to produce innovative market reports tailored for investment professionals, including those in Private Equity, Hedge Funds, Private Credit, and Corporate M&A.
About DiligenceSquared
At DiligenceSquared, we are transforming commercial due diligence for Private Equity funds. Backed by Y Combinator and having successfully raised a substantial Seed round, we are proud to serve some of the globe's largest PE funds. The market opportunity exceeds $10 billion annually, with PE firms spending up to $1 million per report from consulting giants such as McKinsey, BCG, and Bain. Our AI agents streamline this process, delivering faster, cost-effective, and fully auditable results, linking every claim to its source.
Our founding team comprises seasoned professionals from Blackstone and BCG, bringing invaluable insights into the market's needs, which we are now automating.
Your Responsibilities:
Develop comprehensive product features and experiences from start to finish, including database models, API endpoints, and their integration with UI components for our web and AI Voice Agent application.
Design and implement new AI-driven modules from the ground up (e.g., market sizing, competitive analysis) that will become core functionalities of our research platform.
Build and maintain product foundations that include AI agent orchestration, voice AI pipelines, application and API performance, and intelligent automations.
Architect scalable backend services featuring complex asynchronous processing and background task orchestration.
Continuously improve the product by applying insights gained from each project, ensuring we progress by 1% every day (the Law of Compounding is real, especially for a team founded by investment professionals).
Qualifications:
Minimum of 3 years of professional experience in Python backend development.
Proven expertise in building production-ready APIs using frameworks like FastAPI, Django, or equivalent.
Experience in developing agentic systems leveraging large language model platforms (e.g., Anthropic, OpenAI).
Hands-on experience with LLMs in a production environment, focusing on building reliable agentic systems rather than just API calls.
Knowledge of PostgreSQL and SQL database design.
Strong problem-solving and analytical skills with a passion for innovative technology.

