Engineering Manager (AI)

present of AI; San Jose (CA); On-site; USD 170,000 - 260,000; Full time

Job summary

AiPrise is seeking an engineering manager to lead an AI team focused on compliance-focused agent systems. You will hire, mentor, and grow engineers while delivering robust AI capabilities with a strong emphasis on accuracy and reliability.

In this role you will stay close to the code, shaping prompts, tool design, and evaluation processes. You’ll balance speed with correctness and coach the team through ambiguous problems in a fast-evolving space.

Qualifications

• Experience hiring and developing engineers.
• Proven delivery leadership in AI projects.
• Hands-on technical depth in agent systems, prompts and evaluations.
• Ability to balance speed with accuracy in a compliance setting.

Responsibilities

• Lead and mentor an AI engineering team.
• Align delivery with product goals and timelines.
• Oversee design of agent architectures, prompts and evaluation frameworks.
• Ensure reliability and compliance in fintech/ marketplace contexts.

Skills

People management

Hiring

Delivery leadership

Agent systems

Prompts & evaluations

Hands-on coding

Cross-functional collaboration

Job description

An engineering manager for an AI team typically needs a mix of people leadership and hands on technical depth. A strong candidate brings experience hiring and developing engineers, running delivery, and staying close to the code on agent systems, prompts and evaluations. For a compliance verification platform serving fintechs and marketplaces, sound judgment about accuracy and reliability matters as much as speed.

How it fits the AI era

AI shifts much of the routine building and review work toward faster drafting and checking, so the manager spends more time on design choices, quality bars and judgment calls. Agent architectures, prompt and tool design, and evaluation quality still need human ownership because errors carry real consequences in compliance. The human core is deciding what good looks like and coaching people through ambiguous problems.

How it builds AI experience

The role offers hands on exposure to agent design, prompt and tool definition, and evaluation debugging in a compliance setting. That builds practical skill in making AI systems reliable and auditable rather than just capable. Building this means working directly with evals, failure analysis and review of model outputs on real verification tasks.

Worth showing

• People management and hiring
• Prompt and tool review
• Compliance aware engineering

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 AiPrise

An AI compliance platform that verifies businesses and individuals across the world, so fintechs and marketplaces can onboard customers in minutes instead of weeks, according to the company.