Sphinx (YC F24)
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Co-Founder & CEO @ Sphinx (YC F24) | MIT
Background Before you can move money or open an account, someone has to make sure you’re not a criminal. That’s compliance – and it’s broken. Why Join Sphinx Massive, unsexy market:
Banks spend $50B a year hiring thousands of analysts to review alerts and fill out reports by hand. The space has seen very little innovation, and customers complain about our most well-funded competitors weekly. It's not glamorous – until you realize you're building the intelligence layer that protects the entire financial system. We have never lost a deal to a competitor : Yes you heard that right, we’ve won every RFP we’ve been in. Small team, big surface area:
Our co-founders previously sold an AI company & have built ML systems that scaled to millions of users and closed deals with major banks. The rest of our team in SF includes PhDs, industry experts, and competitive coders. Hard tech:
we’re going from zero to one; our tech is our moat. Zero startup bullshit:
we’re not chasing investors, we’re chasing customers. We’re trusted by leading banks and fintechs across the U.S., Canada, Europe, and LatAm. They’ve seen 90% less manual work, 4× lower costs. Technical Challenges Most financial crime data isn't accessible via APIs – it lives in legacy systems, government portals, and third-party platforms. We're building agents that navigate these systems like humans do: clicking, scrolling, interpreting unstructured data, and adapting to interface changes. This requires computer vision, DOM understanding, and robust error handling at scale. The Global Risk Graph Risk doesn’t stop at borders, and neither can we. Our agents operate across languages and regulations, reconciling entities hidden behind shell structures and mismatched disclosures. Each check enriches a single, evolving graph of people, companies, and signals — a global risk intelligence network that never forgets. Decisions at the Speed of Money Payments don't wait for compliance. We process risk signals at the same speed money moves – millions of transactions, thousands of entities, sub-second decisions. Doing this right on AWS means distributed inference, caching, queue orchestration, and self-healing data pipelines. Deep Research without Hallucinations Out-of-the-box deep research agents easily confuse entities that look similar. ChatGPT isn’t going to be able to tell us whether John Smith is a terrorist. We’re building our own deep research pipeline to ensure LLMs don’t mix up facts from different people/companies. What We Look For You solve problems end-to-end:
Our team owns features vertically. You'll architect agent behaviors, build backend systems, optimize ML pipelines, and ship product features – often in the same week. You have a high bar for quality:
In financial crime, "mostly working" isn't good enough. You obsess over edge cases, build robust error handling, and ship systems that institutions trust with billions in transactions. You want to push AI agent capabilities:
We're at the frontier of what's possible with AI agents in production. You'll experiment with the latest models, design novel agentic workflows, and solve problems that don't have Stack Overflow answers. You communicate with clarity:
We move fast with minimal process. You need to articulate tradeoffs, communicate blockers, and make technical decisions with limited information. You're energized by impact:
Our customers protect the financial system from criminals. Your code directly prevents money laundering and terrorism financing. That matters. You hate meetings : You would much rather focus your time on building, being productive, and shipping code About the Interview Technical screening / take-home Deep-dive technical interview (no live coding) Short paid in-person trial Lunch, dinner and snacks at the office ✈️ Paid relocation & one-month temporary housing Latest tech and as many monitors as you can fit on a desk Seniority level
Entry level Employment type
Full-time Job function
Engineering and Information Technology Industries: Technology, Information and Internet Referrals increase your chances of interviewing at Sphinx (YC F24) by 2x Sign in to set job alerts for “Member of Technical Staff” roles.
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#J-18808-Ljbffr
Background Before you can move money or open an account, someone has to make sure you’re not a criminal. That’s compliance – and it’s broken. Why Join Sphinx Massive, unsexy market:
Banks spend $50B a year hiring thousands of analysts to review alerts and fill out reports by hand. The space has seen very little innovation, and customers complain about our most well-funded competitors weekly. It's not glamorous – until you realize you're building the intelligence layer that protects the entire financial system. We have never lost a deal to a competitor : Yes you heard that right, we’ve won every RFP we’ve been in. Small team, big surface area:
Our co-founders previously sold an AI company & have built ML systems that scaled to millions of users and closed deals with major banks. The rest of our team in SF includes PhDs, industry experts, and competitive coders. Hard tech:
we’re going from zero to one; our tech is our moat. Zero startup bullshit:
we’re not chasing investors, we’re chasing customers. We’re trusted by leading banks and fintechs across the U.S., Canada, Europe, and LatAm. They’ve seen 90% less manual work, 4× lower costs. Technical Challenges Most financial crime data isn't accessible via APIs – it lives in legacy systems, government portals, and third-party platforms. We're building agents that navigate these systems like humans do: clicking, scrolling, interpreting unstructured data, and adapting to interface changes. This requires computer vision, DOM understanding, and robust error handling at scale. The Global Risk Graph Risk doesn’t stop at borders, and neither can we. Our agents operate across languages and regulations, reconciling entities hidden behind shell structures and mismatched disclosures. Each check enriches a single, evolving graph of people, companies, and signals — a global risk intelligence network that never forgets. Decisions at the Speed of Money Payments don't wait for compliance. We process risk signals at the same speed money moves – millions of transactions, thousands of entities, sub-second decisions. Doing this right on AWS means distributed inference, caching, queue orchestration, and self-healing data pipelines. Deep Research without Hallucinations Out-of-the-box deep research agents easily confuse entities that look similar. ChatGPT isn’t going to be able to tell us whether John Smith is a terrorist. We’re building our own deep research pipeline to ensure LLMs don’t mix up facts from different people/companies. What We Look For You solve problems end-to-end:
Our team owns features vertically. You'll architect agent behaviors, build backend systems, optimize ML pipelines, and ship product features – often in the same week. You have a high bar for quality:
In financial crime, "mostly working" isn't good enough. You obsess over edge cases, build robust error handling, and ship systems that institutions trust with billions in transactions. You want to push AI agent capabilities:
We're at the frontier of what's possible with AI agents in production. You'll experiment with the latest models, design novel agentic workflows, and solve problems that don't have Stack Overflow answers. You communicate with clarity:
We move fast with minimal process. You need to articulate tradeoffs, communicate blockers, and make technical decisions with limited information. You're energized by impact:
Our customers protect the financial system from criminals. Your code directly prevents money laundering and terrorism financing. That matters. You hate meetings : You would much rather focus your time on building, being productive, and shipping code About the Interview Technical screening / take-home Deep-dive technical interview (no live coding) Short paid in-person trial Lunch, dinner and snacks at the office ✈️ Paid relocation & one-month temporary housing Latest tech and as many monitors as you can fit on a desk Seniority level
Entry level Employment type
Full-time Job function
Engineering and Information Technology Industries: Technology, Information and Internet Referrals increase your chances of interviewing at Sphinx (YC F24) by 2x Sign in to set job alerts for “Member of Technical Staff” roles.
Software Engineer, Fullstack, Early Career
San Francisco, CA $126,000.00-$180,000.00 5 days ago Software Engineer, Infrastructure, Early Career
San Francisco, CA $126,000.00-$155,000.00 1 day ago San Francisco County, CA $108,000.00-$135,000.00 1 hour ago San Francisco, CA $150,000.00-$177,000.00 1 day ago San Francisco, CA $180,000.00-$280,000.00 5 days ago San Francisco, CA $150,000.00-$250,000.00 7 hours ago San Francisco, CA $148,800.00-$223,200.00 4 days ago San Francisco, CA $120,000.00-$150,000.00 1 day ago Redwood City, CA $120,000.00-$170,000.00 14 hours ago San Francisco, CA $120,000.00-$190,000.00 11 months ago Alameda, CA $130,000.00-$160,000.00 4 months ago Software Engineer, Frontend (All Levels)
San Francisco, CA $150,000.00-$220,000.00 2 weeks ago San Francisco, CA $120,000.00-$150,000.00 1 month ago San Francisco, CA $130,000.00-$185,000.00 5 months ago Software Engineering, Frontend (Slack - Multiple levels)
San Francisco, CA $172,000.00-$334,600.00 1 day ago San Francisco, CA $105,000.00-$160,000.00 1 day ago San Francisco, CA $150,000.00-$230,000.00 7 months ago San Francisco, CA $230,000.00-$320,000.00 2 weeks ago San Francisco, CA $155,000.00-$225,000.00 2 weeks ago San Francisco, CA $150,000.00-$250,000.00 1 year ago San Francisco, CA $163,200.00-$223,200.00 2 weeks ago San Francisco, CA $140,000.00-$180,000.00 1 day ago We’re unlocking community knowledge in a new way. Experts add insights directly into each article, started with the help of AI.
#J-18808-Ljbffr