Staff Engineer

Penguin Ai

28d

About The Position

The Staff Engineer identifies high-impact problems and drives solutions through to completion. This role shapes technical direction using evidence, sets a high standard for code and production systems, makes AI a reliable part of engineering work, and helps raise the capabilities of engineers and the hiring bar. The Staff Engineer works with system owners and technical leaders across departments, leads projects end to end, and represents engineering to internal and external customers. The role owns production reliability, operability, and long-term system health, including preventing incidents through observability and tested recovery and addressing root causes. During production issues, the Staff Engineer takes ownership, communicates calmly, drives resolution, and reviews systems and decisions. They also coach engineers, encourage open design discussions, document decisions and uncertainties, and use AI tools responsibly with appropriate review and verification. The company describes itself as an AI-focused healthcare company and emphasizes delivering work that can transform healthcare and save lives. The position requires a bachelor's degree in a relevant field. Compensation and benefits include a competitive salary, medical, vision, and dental coverage, a generous vacation policy, and company holidays.

Requirements

Expert-level use of AI coding tools, such as Claude, Gemini, Copilot, Cursor, Windsurf, or Codeium.
Bachelor’s degree in Computer Science, Engineering, Data Science, or a related field.
Ability to drive technical direction with evidence-backed ideas.
Ability to produce code and designs that are correct, tested, secure, and maintainable.
Ability to identify and manage technical debt, including naming its cost and owning a plan to repay it.
Ability to communicate risks, slips, and mistakes promptly and propose a way forward.
Ability to engage in technical disagreement, welcome challenge, and change position when evidence proves it wrong.
Ability to select simple solutions in light of business priorities and defer lower-priority work.
Openness to acknowledging knowledge gaps and learning what is needed.
Commitment to continually improving engineering practices.

Nice To Haves

Delivered AI or automation projects with measurable impact.
Experience thriving in a high-growth startup.
Ability to translate between product, clinical, and executive language.
A strong track record of turning struggling projects around.

Responsibilities

Identify business constraints and advocate for solutions with decision-makers, then drive agreed fixes across the systems involved.
Lead projects end to end, delegate to support others’ growth, unblock team members, and take responsibility for the team’s output.
Set engineering direction with other technical leaders and define tools, libraries, and practices across departments.
Build measurements when data is unavailable and document alternatives and trade-offs.
Share designs early and document the reasoning behind decisions and what was unknown at the time.
Write code for the team’s hardest problems and review code promptly and constructively.
Own production systems’ reliability, operability, and long-term health; build observability and tested recovery, prevent incidents, and fix root causes.
Take ownership of production incidents, communicate early and calmly, drive fixes to completion, and review systems and decisions rather than individuals.
Use AI throughout engineering work and establish with peers where AI output can be trusted, where it needs closer review, and what must be verified.
Represent engineering to internal and external customers, explaining trade-offs and bringing the team along.
Coach engineers with direct, empathetic feedback, shared learning from mistakes, and challenging work opportunities.
Evaluate candidates and colleagues against consistent evidence-based engineering standards.
Choose simple solutions appropriate to needs and business priorities, deferring work that does not yet merit investment.
Surface risks, delays, and personal mistakes promptly, along with a proposed way forward.
Engage technical disagreements, revise views when evidence warrants it, and escalate when agreement cannot be reached.
Ensure code and designs are correct, tested, secure, and maintainable; identify technical debt costs and own repayment plans.
Continuously improve engineering practices and retire practices that no longer hold up.