Member of Technical Staff Backend

Member of Technical Staff (Backend) San Francisco, CA Compensation: $150,000 – $280,000 + Competitive Equity Type: Full-Time Visa Sponsorship: H-1B, O-1, OPT Priority: High (Hiring Multiple)About 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 6-month roadmap. Client’s 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 systems.Key company highlights:- Has never lost an RFP to a competitor.- Used across the U.S., 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 high-velocity, customer-focused, no-nonsense environment.About the Role — Member of Technical Staff (Backend) As a backend engineer, you will build and maintain the backend and ML systems powering Client's AI agents. These systems navigate the web, interpret unstructured data, detect global financial risk, and make sub-second compliance decisions. The role covers backend engineering, distributed systems, ML pipelines, and agent workflows. You will own features end-to-end and ship production systems used by banks.This role is ideal for engineers seeking:- High technical scope- Challenging problems with real-world 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 languages.3. Decisions at the Speed of Money - Build infrastructure that processes millions of transactions on AWS, including: - Distributed inference - Caching - Queue orchestration - Self-healing 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 ChatGPT.What You’ll Do- Architect and ship backend systems used by AI agents.- Build ML/agent pipelines, distributed inference, and automation frameworks.- Own features vertically: design → build → test → deploy → iterate.- Handle large-scale data, global risk signals, and compliance edge cases.- Experiment with frontier AI models and agentic architectures.- Collaborate directly with founders, researchers, and customers.Requirements- 2–8+ years of software engineering experience. (preferred 4-8yrs)- 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 needed.Green 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 early-stage startup experience.- Competitive programming background.- Open-source contributions or strong GitHub projects.- Experience in AML/KYC/financial crime domains.Red Flags (Avoid)- Pure data scientists without engineering depth.- Academic/research profiles lacking production experience.- No hands-on deployment experience.Interview Process1. Intro call (fit & motivation)2. Technical screen / take-home3. Deep-dive technical interview (no live coding)4. 2-day paid in-person trial5. Offer 🎉Benefits & Perks- Lunch, dinner & 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.

Member of Technical Staff (Backend)
San Francisco, CA
Compensation: $150,000 – $280,000 + Competitive Equity
Type: Full-Time
Visa Sponsorship: H-1B, O-1, OPT
Priority: High (Hiring Multiple)

About 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 6-month roadmap. Client’s 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 systems.

Key company highlights:
- Has never lost an RFP to a competitor.
- Used across the U.S., 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 high-velocity, customer-focused, no-nonsense environment.

About the Role — Member of Technical Staff (Backend)
As a backend engineer, you will build and maintain the backend and ML systems powering Client's AI agents. These systems navigate the web, interpret unstructured data, detect global financial risk, and make sub-second compliance decisions. The role covers backend engineering, distributed systems, ML pipelines, and agent workflows. You will own features end-to-end and ship production systems used by banks.

This role is ideal for engineers seeking:
- High technical scope
- Challenging problems with real-world impact
- Minimal meetings
- A small team with high autonomy
- Opportunities to push the frontier of AI agents in production environments

Key Technical Challenges
1. 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 scale

2. Global Risk Graph
- Develop a unified intelligence layer connecting people, companies, and risk signals across jurisdictions and languages.

3. Decisions at the Speed of Money
- Build infrastructure that processes millions of transactions on AWS, including:
- Distributed inference
- Caching
- Queue orchestration
- Self-healing data pipelines

4. 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 ChatGPT.

What You’ll Do
- Architect and ship backend systems used by AI agents.
- Build ML/agent pipelines, distributed inference, and automation frameworks.
- Own features vertically: design → build → test → deploy → iterate.
- Handle large-scale data, global risk signals, and compliance edge cases.
- Experiment with frontier AI models and agentic architectures.
- Collaborate directly with founders, researchers, and customers.

Requirements
- 2–8+ years of software engineering experience. (preferred 4-8yrs)
- 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 needed.

Green 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 early-stage startup experience.
- Competitive programming background.
- Open-source contributions or strong GitHub projects.
- Experience in AML/KYC/financial crime domains.

Red Flags (Avoid)
- Pure data scientists without engineering depth.
- Academic/research profiles lacking production experience.
- No hands-on deployment experience.

Interview Process
1. Intro call (fit & motivation)
2. Technical screen / take-home
3. Deep-dive technical interview (no live coding)
4. 2-day paid in-person trial
5. Offer 🎉

Benefits & Perks
- Lunch, dinner & snacks at the office
- Comprehensive healthcare
- Unlimited PTO
- Annual company offsite (last: Mexico)
- Paid relocation + 1 month temporary housing
- Latest tech + multiple monitors


Biggest Note
- Candidates who are senior and strong in architecture are almost certain to be shortlisted.