Product Engineer

Senior Product Engineer, Compliance AI

Remote – United States

$200,000 - $250,000 + 0.2%-0.4%

Your opportunity

Our client is a well-financed, seed-stage startup building a platform of agents that automate financial crime investigations and compliance workflows. The company is a Delaware corporation that currently operates with remote teams distributed across the United States. The founders and several early team members are located in San Francisco, and the company will be establishing a workspace there in the medium term.

They are a hard-charging startup that has raised $6.2M, grew to $1M in ARR in under one year, and has marquee clients around the globe including Kraken (US), Koho (Canada), and Viva (EU).

Their product enables customers to invoke (or “hire”) agents that automate AML, sanctions screening, adverse media monitoring, KYC, and transaction screening and monitoring. The solution combats revenue losses that result from high-friction customer onboarding and the rising costs of compliance missteps, and allows growing businesses to scale revenues rapidly without making compliance tradeoffs. The product is not versioned for customers, and the engineering team deploys daily.

The company is led by an experienced founder who has raised more than $100M to date and has grown their last venture to a $1.5B valuation. Both the founder and CTO have led fintechs that required large compliance teams and have had outlier experience in the domain. As of November 2025, the company does not yet have any direct competitors in its space.

Key responsibilities

• Software architecture and engineering: Design and implement event‑driven, real‑time, highly concurrent systems leveraging advanced concurrency patterns, asynchronous messaging, and performance optimizations to ensure low‑latency, high‑throughput and fault‑tolerance

• Systems architecture and engineering: Collaborate on cloud‑native architecture, infrastructure as code, CI/CD pipelines, autoscaling and load‑balancing strategies, security best practices, and observability efforts

• AI platform engineering: Integrate LLMs and other emerging AI technologies, select and potentially fine‑tune models, orchestrate deployments, and monitor performance

• Technical leadership and mentoring: Guide architecture and design decisions, conduct code reviews, establish best practices, and coach team members to accelerate their technical growth while reinforcing a culture of continuous improvement

Tech stack

• Back-end: Python (FastAPI), Go

• Front-end: React/Next.js

• Database: Cloud SQL, Big Query, Alloy
  
  DB, GCS

• Infrastructure: GCP, Azure

• ML & AI services: OpenAI

• Containers: Kubernetes/GKE

Your know-how

• You are comfortable across the stack with deep architectural experience in large-scale distributed systems and data management

• You have a strong product mindset and are comfortable working iteratively with fuzzy requirements

• You have experience scaling backend infrastructure and are very comfortable with at least one major cloud provider

• You have a bias to action and subscribe to the gettings things done (GTD) engineering methodology

• You have experience building production services/APIs in Python

• You have a fantastic command of English

It’s a bonus if

• You have experience scaling a fast-growing AI and/or B2B SaaS venture

• You have financial compliance domain experience

• You have experience shipping LLM-enabled products/features to production