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Saris AI logo

Engineering Manager

Posted 2 months ago

RemoteSan Francisco


About Saris AI

We're a San Francisco, Montreal and Toronto based applied AI startup that's building the future of work in the banking industry. We are tackling a $100 billion/yr problem, doubling every quarter and pushing the boundaries of what's possible with multi-turn AI agentic systems.

Our goal is to tackle the type of automation problems that require long-context reasoning, tool orchestration across legacy systems, and strict compliance loops: the ones without known answers.

We've shipped real agents that handle real customer workflows in production. With a growing customer base and live deployments, we're scaling up fast and looking for deeply technical builders who want to have outsized impact early.

Our core engineering team is looking for a hands-on Engineering Manager who thrives in early-stage, ambiguous environments. You've built and led engineering teams, owned delivery end-to-end, and know what it takes to ship high-quality software in a fast-moving AI-native environment.

Your mission is to

  • Lead a product engineering team building AI-native financial infrastructure for banks and credit unions

  • Own delivery, engineering quality, and the operating cadence for your team

  • Scale the team by hiring, onboarding, and ramping engineers to achieve a consistently high

  • Develop engineers through regular coaching, direct feedback, and individualized growth plans that help people level up and take on bigger roles

  • Partner with Product, ML, and executive leadership on technical strategy and roadmap

  • Establish engineering management best practices across sprint rituals, release processes, and incident response that the org can build on as it scales

Who You Are

  • 7+ years of engineering experience, including 2+ years managing engineering teams in a product context

  • Strong enough technically to evaluate architecture decisions, guide trade-offs, and get into the code when it matters

  • Fluent in AI/ML systems: You understand LLM behavior, eval frameworks, and prompt engineering well enough to guide how AI gets built into the product, not just how to use AI tools personally

  • Proven track record of developing team members

  • Execution-focus: you ship, hold the team accountable, manage scope aggressively, and don't wait for perfect information to move

  • Experience building teams or processes from scratch, not just inheriting and optimizing someone else's

  • Comfortable operating with high autonomy in ambiguous, early-stage environments where you'll wear multiple hats

  • Clear communicator who translates technical complexity for stakeholders and business context for engineers

Bonus Points If You

  • Have shipped AI or LLM-powered systems in production, particularly in a regulated industry (financial services, healthcare, etc.)

  • Have experience with eval frameworks, prompt versioning, or ML observability tooling

  • Have hired and built a team from the ground up, owning the full recruiting funnel from sourcing through close

  • Have worked in a Series A / early-stage environment where the playbook didn't exist yet


Why Join Saris AI?

  • ๐Ÿฆ Join us in building the future of work for the trillion-dollar banking industry using cutting edge AI technology.

  • ๐Ÿ‘ฅ Join as one of the first engineering leaders โ€” your decisions will define how engineering management works at Saris for years.

  • ๐Ÿค– Manage engineers building production AI in regulated finance โ€” your team works with LLMs, evals, and agentic systems where outputs need to be auditable, compliant, and correct.

  • ๐Ÿ’ฒ Competitive compensation with premium benefits and equity package.

  • ๐Ÿค Work with a stellar team of engineers, builders, and leaders; including repeat YC founders with a successful exit (Ready Education).

  • ๐Ÿ“ˆ We already have production agents live with revenue-generating customers.

Job details
Workplace
Remote
Location
San Francisco

Automate complex back-office workflows across lending, operations, and compliance with institutional control.

Key team members

Carlos Delatorre

Carlos Delatorre

Brian Kneafsey

Brian Kneafsey

Marc Wendling

Marc Wendling

Keisuke Shingu

Keisuke Shingu

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