Engineering Manager

present of AI; San Francisco (CA); On-site; USD 180,000 - 270,000; Full time

Benefits offered by this job

Competitive salary

Stock options

Medical insurance

Job summary

present of AI is seeking a Senior Engineering Manager in San Francisco to lead a small full‑stack team while hands-on coding. You will own the most challenging technical problems and guide discussions with founders, customers, and engineers, ensuring robust cloud-based production systems.

The role emphasizes grounding AI agents in real customer data, scalable debugging, and building reliable tools for finance-related workflows. Location is San Francisco, with on-site expectations.

Qualifications

• Proven track record shipping production systems on cloud infrastructure.
• Experience leading projects across engineers and communicating tradeoffs to founders and customers.

Responsibilities

• Lead a small team of full stack engineers and stay close to the code.
• Own the hardest technical problems and drive end-to-end delivery.
• Set the bar through design reviews and pairing sessions.
• Communicate tradeoffs clearly to founders and customers.

Education

Bachelor's degree in Computer Science

Leadership

Full stack development

Cloud infrastructure

Code reviews

Pair programming

Stakeholder communication

Production debugging

Mentoring

Tools

AWS

GCP

CI/CD

Containerization

Monitoring/Observability

Job description

Engineering · San Francisco · FullTime · Senior level

This is a hands on manager role that stays close to the code. The person leads a small team of full stack engineers while spending most of the week building, owning the hardest technical problems, and setting the bar through reviews and pairing. A strong candidate has shipped and debugged production systems on cloud infrastructure, has led projects across other engineers, and can explain tradeoffs to founders and customers as easily as to the team.

How it fits the AI era

The product is built on AI agents that read and act on financial data inside old systems that were never meant to be queried. Much of the engineering judgment sits in grounding the agents in a customer's real numbers, deciding what stays a fixed pipeline versus what a model handles, and judging quality when the right answer lives in a decades old system. The human parts are scoping, sequencing, and the hard debugging when third party systems fail.

How it builds AI experience

Working here means building agents over proprietary connections into on premise accounting systems, so the AI experience gained is practical: tool design over internal APIs, evaluation of agent output against real customer data, and reliability work at scale. Someone preparing for this could build small agents that read and reconcile messy records, and practice measuring when their output is actually correct.

Worth showing

• Cloud infrastructure
• Hard debugging end to end
• Leading small teams
• Clear tradeoff communication

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 Agave

AI that reads, codes and syncs invoices, expenses and vendor compliance documents across the patchwork of accounting systems construction contractors use.