Member of Technical Staff (Backend)
Location: San Francisco CA
Compensation: $150000 $280000 Competitive Equity
Type: Full-Time
Visa Sponsorship: H-1B O-1 OPT
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. 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 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 Clients 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
- 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
Develop a unified intelligence layer connecting people companies and risk signals across jurisdictions and languages.
- 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
- 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 Youll 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
- 28 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.
Member of Technical Staff (Backend) Location: San Francisco CA Compensation: $150000 $280000 Competitive Equity Type: Full-Time Visa Sponsorship: H-1B O-1 OPT About The Company Client is automating compliance for banks and fintechs using AI agents that function like human analysts within browsers....
Member of Technical Staff (Backend)
Location: San Francisco CA
Compensation: $150000 $280000 Competitive Equity
Type: Full-Time
Visa Sponsorship: H-1B O-1 OPT
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. 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 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 Clients 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
- 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
Develop a unified intelligence layer connecting people companies and risk signals across jurisdictions and languages.
- 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
- 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 Youll 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
- 28 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.
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