Salary / Hourly Rate: $375,000 - $375,000 per year
Benefits: In-person SF team; high ownership on a 5-person, seed-stage startup.,Meaningful equity; fast path to scope as the product/function owner.,US Citizens Only,Open to Exceptional New Grads
Role Information
Role Overview: N/A
Responsibilities: Transform Prototypes into Production Systems: Serve as the crucial link between visionary product concepts and their execution, ensuring high-quality, robust systems that adhere to production standards., Design and Implement Toolchains: Develop efficient workflows and toolchains that enable AI agents to enhance software engineering tasks, focusing on reliability and precision., Develop Evaluation and Safety Protocols: Establish practical evaluation scenarios with robust criteria, integrating safety standards and fail-safes to ensure optimal performance., Full-Stack System Development: Architect and implement both the backend (Python) and frontend (TypeScript/React) components of the platform, facilitating seamless AI-driven workflows., Safety-First System Design: Implement comprehensive safety mechanisms, including risk detection, fallback paths, and human-in-the-loop protocols for escalations, making system safety a top priority., Create and Maintain Internal Tools: Develop and refine lightweight internal tools and APIs to streamline operations and improve feedback loops within the engineering team., Cross-Disciplinary Collaboration: Collaborate with design and clinical research teams to incorporate user experience insights and research findings into the product, ensuring the translation of insights into actionable product advancements., Foster a Rapid Shipping Culture: Lead efforts to maintain a dynamic, fast-paced development environment, focusing on quick iterations, robust evaluations, and consistent, high-quality releases.
Qualifications: 0-2 years of experience as a software engineer and can code in python., We are optimized for builders: you have shipped real products (internships or full-time) and you love the loop of design → measurement → iteration in a small-team environment., Strong software engineering fundamentals: you’re fluent in Python and you have hands-on experience with full-stack development (TypeScript/React or equivalent). You’ve built tools/features that real users touched, not just prototypes., Product-sense plus speed: you can simplify ambiguous problems into pragmatic baselines, deliver value in days (not quarters), and iterate rapidly while maintaining high standards., Experience with system quality and safety: you have built guardrails (error detection, fallback paths, monitoring), and you are comfortable being accountable for production quality—not just writing code, but delivering sustained value., Evidence-driven mindset: you instrument features, define measurable outcomes (not just engagement), and iterate based on data and feedback loops., Collaboration in high-trust, high-ownership teams: you thrive building in-person with founders and cross-functional partners (design/research). You’re excited to raise questions, shape architecture, and drive new standards., Location & work-auth fit: In-person in San Francisco is required; US work authorization (no sponsorship) is required., Bonus: Prior internship or experience at a top-tier tech or startup, and/or degree from a highly ranked engineering school.
Minimum Requirements: In-person in San Francisco (team works onsite),Must be legally authorized to work in the United States now and for the foreseeable future without employer sponsorship.,Proven track record of shipping software features end-to-end
Screening Questions: (Optional Video). This step is completely optional. If you’d like, record a short 2–3 minute video introducing yourself and your experience — or share a recording of your interview with the recruiter if that’s easier. You can upload the link via Loom or Google Drive. This just helps us get to know you better, but there’s no pressure if you’d prefer to skip it.,(Optional Portfolio / GitHub) If available, please share a link to your GitHub, portfolio, or any recent projects you’ve worked on. This is entirely optional but helps provide more context about your work.,Why this role? What about our mission and our in-person San Francisco team resonates with you?
Company Information
About Company: N/A
Culture: N/A
Additional Information
Interview Process: Step 1: Vibe check call (~15 minutes) A quick introduction to align on mission, confirm in-person San Francisco work suitability, and verify US work-authorization fit. Step 2: Technical take-home (~4 hours, compensated) Candidates build a small full-stack feature or evaluation pipeline relevant to voice + text workflows (e.g., prompt/agent design, tool use/ function-calling, safety checks). Provide notes on trade-offs and what you’d test next. Step 3: Technical deep-dive & code review (~30-45 minutes) Walk through the take-home plus 1–2 shipped or live agent/LLM features. Explore prompts, evaluation loops, latency/turn-taking handling, and how you measured quality and reliability. Step 4: In-person trial in San Francisco (1–2 days, paid) Work onsite with founders on a scoped feature: prototype → evaluate → harden → ship. We assess clarity, speed, product sense, how you reason about safety and measurable outcomes, and your ability to collaborate in-person with our team. Step 5: Offer Fast debrief, reference check if needed, and compensation/equity discussion aligned with our listed range.
Day to day: You will work at the frontier of what software engineering could be, designing, building and shipping the core features of a simulation environment where AI agents execute full-stack engineering workflows. On any given day you’ll write Python and TypeScript/React code, build pipelines, design evaluation loops, and partner with founders to move quickly from prototype to release. You’ll build tools around agent prompting and feedback, add guardrails and observability, and ensure what you ship has measuring real outcomes— not just ticking boxes.
Team: Work directly with the three founders on a ~5-person team in person in San Francisco. You’ll pair with design on voice/chat UX and with research on measurement and risk mitigation, keeping feedback loops tight and decisions pragmatic. (YC lists skills as Prompt Engineering, Python; the culture emphasizes on-site collaboration.)
Growth: As one of the early engineers you’ll not just execute—you’ll help define the standards: architecture for agent workflows, tooling for evaluation and monitoring, and practices for shipping safe, reliable systems. You’ll set the technical direction and have the ability to lead new domains as the company scales. This is more than a job—it’s a career accelerator. You’ll gain ownership, deep technical responsibility, and the chance to grow into a major engineering leader in a next-gen company.
Ideal Candidate Profile: You’ve shipped real software (internship or full-time) and played a substantial role in the lifecycle: discovery → design → implementation → iteration., You’re fluent in back-end engineering (Python) and comfortable across full-stack work in a modern front-end stack (e.g., TypeScript/React)., You’ve worked in production: whether you built tooling, services, UI or infrastructure, you understand trade-offs, can instrument outcomes, and can speak to reliability, performance, and user-impact., You treat safety and quality as features: you’ve designed guardrails, fallback paths, monitoring, or other systems that ensure production code behaves as intended and responsibly., You thrive in a high-ownership, in-person environment: you’re able to collaborate closely with founders and early engineers, raise questions, iterate fast, and help shape how things get built., Bonus: You have experience at a top-tier tech company or startup, or from a competitive engineering program — and you carry a mindset of “I’ll build for the next level, not just the next sprint”., Alex Beal — LinkedIn: linkedin.com/in/beala LinkedIn, Byron Luk — LinkedIn: linkedin.com/in/byron-luk LinkedIn, Polished but unshipped projects with no real end-users or production impact., Candidates unable to commit to in-person work in San Francisco., Little to no experience in safety-oriented systems or conversation/agent-driven workflows.
