Member of Technical Staff - Engineering Lead

present of AI; San Francisco (CA); On-site; USD 180,000 - 260,000; Full time

Job summary

AIUC is seeking a hands-on engineering lead in San Francisco. The role splits roughly between writing code, managing engineers, and hiring, with an emphasis on delivering customer-facing products end to end.

A strong candidate has led engineers directly, co-run half a team with another lead, and communicates clearly to align design decisions with product strategy. Startup or founder experience is a plus.

Qualifications

• Shipped customer-facing products end to end.
• Hands-on in Node/TypeScript/Python.
• Co-leading a team with direct reports and hiring experience.
• Startup or founder experience is a plus.

Responsibilities

• Lead engineering efforts for AI risk tooling and product features.
• Directly manage engineers, mentor growth, and hire as needed.
• Collaborate with product and design to align technical decisions with strategy.

Skills

Node.js

TypeScript

Python

Team leadership

Job description

Member of Technical Staff - Engineering Lead

AI & Data · San Francisco · FullTime · Senior level

This is a hands on engineering lead role split roughly evenly between writing code, managing engineers, and hiring. A strong candidate has shipped customer facing products end to end, managed engineers directly, and worked inside a codebase someone else built, ideally with startup or founder experience. The person also needs to co run half a team with another lead, sharing reports and hard decisions, so trust and direct communication matter as much as technical depth.

How it fits the AI era

The product itself is AI facing: a system that stress tests AI agents for risks and attacks, so the engineering work sits close to how AI systems fail. AI can speed up parts of building and testing, but judgment about what to certify, where the product goes after general availability, and how to grow a team stays with people. The role keeps a human in the loop on product direction and on the trust the company sells.

How it builds AI experience

Working here means building tooling that probes AI agents for security and financial risk, which builds practical understanding of how agents behave under attack. A candidate can strengthen that by studying how agents are tested and red teamed, and by getting familiar with the kinds of failures certification aims to catch. The posting notes deep machine learning work sits with a separate lab team, so this is applied AI exposure rather than model building.

Worth showing

• Shipped products end to end
• Hands on Node TypeScript Python
• Co leading a team
• Startup or founder experience

This is our own read, written from the employer's posting and the company's Spotlight. The employer's posting is the source of truth for the role.

About AIUC

AIUC certifies AI agents against its AIUC-1 standard and underwrites liability tied to audit outcomes, per the company.