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Sphinx

Forward Deployed Engineer

San Francisco, California, United States

Location
San Francisco, California, United States
Work
On-site
Employment
Full-time
Level
Not stated
Function
Engineering
Pay
$120K – $200K a year
Posted
12 months ago

Pay and the market here

The top of this role’s range, $200K a year, is 23% below the median of $259K for engineering jobs in San Francisco (middle half $215K – $315K, 4,022 jobs that state pay).

5,003 engineering jobs open in San Francisco: 9% remote, 949 posted in the last 30 days.

Wondering how well you fit this one? OptiTalent Career checks each requirement against your own record, privately. About OptiTalent Career →

About the role

tl;dr: We’re automating compliance for banks and fintechs with AI agents that work like human analysts – on a browser. Demand is growing faster than we can keep up, and we’re expanding our deployment team to meet the needs of major institutions across the U.S., Canada, Europe, and LatAm. If you love shipping real systems in live environments, solving edge cases in record time, and working directly with clients, we should talk.

PS: want to skip the queue? Save Morty from Rick in our AI-proof coding challenge. If things go well, we'll reach out to organize an interview directly with our CTO. And if you win, we pay you $10k, no questions ask.

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.

Sphinx builds AI analysts that work inside browsers, APIs, and internal systems just like humans — automating AML, KYC, KYB, and transaction monitoring end-to-end.

Our agents already handle millions of compliance decisions across banking, fintech, and crypto. Now, we’re scaling fast, and every new deployment pushes the frontier of what’s possible with AI in production.

Why Join Sphinx

  1. 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.
  2. We don’t lose deals: Yes you heard that right, we’ve won every RFP we’ve been in against our competitors.
  3. 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.
  4. Hard tech: we’re going from zero to one; our tech is our moat.
  5. Zero startup bullshit: we’re not chasing investors, we’re chasing customers. We’re trusted by leading banks and fintechs across the world. They’ve seen 90% less manual work, 4× lower costs.

Technical Challenges

Browser Agents for the Invisible Web

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.

Adapting to Live Client Environments

Every deployment is unique. You’ll design flexible integration layers, map complex workflows, and make agents resilient to interface changes and client-specific quirks. You’ll ship fixes in live environments, build diagnostic tools, and feed learnings back into our product to make every deployment faster and smarter.

Human-AI Collaboration

Work directly with compliance officers and analysts to translate SOPs into structured agent logic – capturing human judgment and turning it into repeatable automation. From first call to production rollout, you’ll lead the full lifecycle of deployments, bridging engineering, product, and client success.

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.

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 build for uptime, obsess over failure points, and ship agents that institutions trust with billions in transactions.
  • You’re comfortable in ambiguity: No two client environments are alike. You enjoy the challenge of figuring things out as you go, and have confidence in your ability to become fluent with our product.
  • You communicate with clarity: You’re the bridge between customers and our codebase. You can translate client needs into precise technical requirements and technical issues into clear explanations.
  • 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 bureaucracy: You’d rather fix the problem than schedule a meeting about it. You’re happiest when you’re building, experimenting, and making things work.

About the Interview

  • Intro call (fit & motivation)
  • Technical screening / take-home
  • Deep-dive technical interview (no live coding)
  • Short paid in-person trial
  • Offer 🎉

Compensation & Benefits

  • 🍽 Lunch, dinner and snacks at the office
  • 🏥 Comprehensive healthcare
  • 🏝️ Unlimited PTO
  • 🗺️ Annual offsite (last one in Mexico)!
  • ✈️ Paid relocation & one-month temporary housing
  • 💻 Latest tech and as many monitors as you can fit on a desk

Source

Posted by Sphinx on their own hiring page, jobs.ashbyhq.com. OptiTalent shows it as published, read 07 Nov 2026 12:01 UTC; the original is the reference.

View the original ad ↗

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