LocationSan Francisco, CA, New York, NY, Portland, OR, or Remote within Canada or United States
Work ModeFully Remote
DepartmentSoftware Engineering
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Posted 2h ago
Teaching hospitals operate on a model that's remained largely unchanged for over a century: residents learn medicine not through lectures alone, but through supervised practice alongside attending physicians who've seen thousands of cases. The attending physician doesn't just demonstrate technique—they narrate their clinical reasoning, point out subtle patterns the resident would miss, and know when to let the resident struggle versus when to intervene. This model works because medicine recognized early that expertise requires both knowledge transfer and judgment development, and judgment only develops through guided repetition.
Software engineering is facing a version of this same challenge. AI coding tools can now produce working code faster than most engineers can type it—but a growing body of research suggests that speed comes at a cost. Engineers who lean heavily on AI during skill formation score significantly lower on debugging and conceptual mastery. The gap is especially pronounced in exactly the skills that matter most for oversight: understanding why code works, catching when it doesn't, and reasoning about what should change. As AI-written code becomes the norm, the engineers who can actually verify, debug, and guide that code become more valuable—not less.
Our Engineering Training team is looking for a software engineer and educator whose primary mission is helping Mercury engineers use AI effectively without eroding the fundamentals that make them effective in the first place. You'll be a part of designing the systems, norms, and learning experiences that turn "AI as accelerant, not dependency" from a slogan into an operational reality—across experience levels, from new hires through senior ICs. You balance pragmatic execution with thoughtful program design, and you're comfortable doing the organizational legwork to drive adoption. This is a unique opportunity to shape what AI-enabled engineering excellence looks like at Mercury.
*Mercury is a fintech company, not an FDIC-insured bank. Banking services provided through Choice Financial Group and Column N.A., Members FDIC.
If this role interests you, we invite you to explore our public demo at demo.mercury.com and read mercury.com/blog/escalating-esqueleto from our training team. If How AI Assistance Impacts the Formation of Coding Skills resonated with you, we'd especially love to talk.
The total rewards package at Mercury includes base salary, equity (stock options), and benefits. Our salary and equity ranges are highly competitive within the SaaS and fintech industry and are updated regularly using the most reliable compensation survey data for our industry. New hire offers are made based on a candidate's experience, expertise, geographic location, and internal pay equity relative to peers.
Our target new hire base salary ranges for this role are the following:
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