Member of Technical Staff Backend San Francisco CA Compensation 150000 280000 Competitive Equity Type FullTime Visa Sponsorship H1B O1 OPT Priority High Hiring MultipleAbout the Company Client is automating compliance for banks and fintechs using AI agents that function like human analysts within browsers The company is experiencing rapid growth and is expanding its engineering team to accelerate development and meet an ambitious 6month roadmap Clients AI agents automate AML KYC KYB and transaction monitoring targeting a 50B market currently dominated by manual compliance labor The company is led by founders with a track record of building and selling successful AI and ML systemsKey company highlights Has never lost an RFP to a competitor Used across the US Canada Europe and LatAm Delivers 90 less manual work and 4 lower costs to customers Run by founders who previously sold an AI company and built ML systems used by millions Operates in a highvelocity customerfocused nononsense environmentAbout the Role Member of Technical Staff Backend As a backend engineer you will build and maintain the backend and ML systems powering Clients AI agents These systems navigate the web interpret unstructured data detect global financial risk and make subsecond compliance decisions The role covers backend engineering distributed systems ML pipelines and agent workflows You will own features endtoend and ship production systems used by banksThis role is ideal for engineers seeking High technical scope Challenging problems with realworld impact Minimal meetings A small team with high autonomy Opportunities to push the frontier of AI agents in production environmentsKey Technical Challenges1 Browser Agents for the Invisible Web Build AI agents that interact with legacy government portals and financial systems using Computer vision DOM reasoning Robust error handling at scale2 Global Risk Graph Develop a unified intelligence layer connecting people companies and risk signals across jurisdictions and languages3 Decisions at the Speed of Money Build infrastructure that processes millions of transactions on AWS including Distributed inference Caching Queue orchestration Selfhealing data pipelines4 Deep Research Without Hallucinations Develop deep research pipelines to ensure LLMs do not confuse similar entities providing accurate compliance decisions beyond the capabilities of generic models like ChatGPTWhat Youll Do Architect and ship backend systems used by AI agents Build MLagent pipelines distributed inference and automation frameworks Own features vertically design build test deploy iterate Handle largescale data global risk signals and compliance edge cases Experiment with frontier AI models and agentic architectures Collaborate directly with founders researchers and customersRequirements 28 years of software engineering experience preferred 48yrs Strong backend engineering background Python preferred Experience with AWS distributed systems or ML pipelines Proven track record of shipping production systems Strong communication skills and ability to operate with minimal process Comfortable interacting with clients when neededGreen Flags Strong Matches Experience with browser automation or computer vision Background in distributed inference and optimization on AWS systems Experience building transactional or financial systems Familiarity with LLM systems and deep research pipelines Prior founder or earlystage startup experience Competitive programming background Opensource contributions or strong GitHub projects Experience in AMLKYCfinancial crime domainsRed Flags Avoid Pure data scientists without engineering depth Academicresearch profiles lacking production experience No handson deployment experienceInterview Process1 Intro call fit amp motivation2 Technical screen takehome3 Deepdive technical interview no live coding4 2day paid inperson trial5 Offer Benefits amp Perks Lunch dinner amp snacks at the office Comprehensive healthcare Unlimited PTO Annual company offsite last Mexico Paid relocation 1 month temporary housing Latest tech multiple monitorsBiggest Note Candidates who are senior and strong in architecture are almost certain to be shortlisted
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