Besimple AI
Expert-in-the-loop eval data for AI
Product Engineering Intern - Remote Part Time
About the role
About Besimple AI
We are a safety data research company. Our mission is to bring AI into the real world safely. We believe that AI can meaningfully empower humanity only if we put safety first. We’re a small, nimble team of passionate builders who believe humans must remain in the loop.
The Role
We’re hiring a high-agency Product Engineering Intern to build and ship real product: fast, beautiful landing websites, full-stack features, and AI-agent workflows used daily by customers. You’ll work directly with the founding team and CTO Bill Wang who had been at Meta for over 7 years. You will own scoped projects end-to-end, and ship to production frequently. Remote, part-time with potential to convert to full-time.
What You’ll Do
- Build landing sites that convert: fast, responsive pages with strong UX, SEO, and analytics (A/B tests, event tracking, funnels).
- Ship full-stack features: from DB/APIs to polished UI. Own scoping, implementation, testing, and release.
- Prototype & wire AI agents: tools/function-calling, eval harnesses, RAG/retrieval, safety/guardrails.
- Dogfood & iterate: instrument, measure, fix, and improve product quality; write lightweight tests; add observability.
- Collaborate: work with the founding team; participate in code reviews/RFCs; document decisions.
Minimum Qualifications
- Landing-site portfolio: links showing fast, responsive, accessible marketing sites with solid UX + instrumentation.
- Full-stack fundamentals: comfortable across frontend + backend; strong TypeScript/JavaScript; Git fluency.
- Hands-on with AI agents: built something that calls tools/functions, retrieves context, or runs simple evals (school/personal/work).
- Ownership & speed: bias to ship, clean code, iterate; self-managed.
- Quality mindset: add tests when it matters, watch metrics, fix regressions, leave code better than you found it.
- Communication: clear written/spoken English; proactive updates and crisp PRs/RFCs.
Nice-to-Haves
- Next.js App Router, server actions, edge functions; shadcn-ui polish
- Design sense (Figma) and component systems; accessibility (a11y)
- Prior startup or open-source contributions
Logistics
- Schedule: 15–25 hrs/week (flexible)
- Location: Remote (U.S.). Occasional travel to SF Bay Area as needed
- Eligibility: Studying or recently graduated from a U.S./Canadian university; US work authorization or CPT/OPT-eligible
Benefits
- Competitive stipend benchmarked to SF remote internships
- Potential full-time conversion with stock options
- Remote-first, high-trust culture; real product ownership
- Letter of recommendation to support your next role
Diversity Statement
Besimple AI is committed to a diverse, inclusive culture. We’re an equal-opportunity employer and welcome applicants from all backgrounds.
About the interview
We will keep it simple! After resume screening, we will invite selected candidates for a coding challenging. Based on the results from the coding challenging, we will invite you to a short interview, and that’s it!
About Besimple AI
Why Us
At Besimple AI, we’re making it radically easier for teams to build and ship reliable AI by fixing the hardest part of the stack: data. Good evaluation, training and safety data require domain experts, robust tooling and meticulous QA. AI teams and labs come to us to get high quality data so they can launch AI safely. We’re a YC X25 company based in Redwood City, CA, already powering evaluation and training pipelines for leading AI companies across customer support, search, and education. Join now to be close to real customer impact, not just demos.
Why This Matters
High-quality, human-reviewed data is still the single biggest driver of model quality, but most teams are stuck with old tools and legacy processes that do not scale to modern, multimodal, agentic workflows. Besimple replaces that mess with instant custom UIs, tailored rubrics, and an end-to-end human-in-the-loop workflow that supports text, chat, audio, video, LLM traces, and more. We meet teams where they are—whether they need on-prem deployments and granular user management or a fast cloud setup—to turn evaluation into a continuous capability rather than a one-time project.
Traction & Customers
Who You’ll Work With
Founders previously built the annotation platform that supported Meta’s Llama models. We’ve seen how world-class annotation systems shape model quality and iteration speed; we’re bringing those lessons to every AI team that needs to ship with confidence. You’ll work directly with the founders and users, owning problems end-to-end—from an interface that unlocks a tough rubric, to a workflow that reduces disagreement, to a AI judge system that improves quality.
How We Work
- Bias to shipping and learning with customers
- Respect for craft: calibration, rubric clarity, inter-annotator agreement (IRR)
- Tight feedback loops from production back to evaluation
- Ownership: you’ll shape evaluation as an engineering discipline with real “fail-to-ship” tests tied to business and safety goals
If you’re excited by systems that combine product design, human judgment, and applied AI—and you want to build the data and evaluation layer that keeps AI trustworthy—come build with us. See how fast teams can go from raw logs to a robust, human-in-the-loop eval pipeline—and how that changes the way they ship AI.
