About Us
We are partnering with two seasoned Silicon Valley entrepreneurs and executives who have scaled startups from inception to IPO, led successful exits to Fortune 500 companies, and tripled the valuation of publicly traded firms in record time. The company is backed by a top‑tier Silicon Valley venture capital firm and prominent angels from Anthropic, Google DeepMind, NVIDIA, ARM, and Oracle AI, among others. Although we are technically a seed‑stage company, the amount raised and current valuation place us on par with a typical Series A company. We are a fast‑moving AI startup building ambitious products at the intersection of web applications and modern AI. We are creating a next‑generation personalization experience that seamlessly enhances everyday life — delivering truly magical, meaningful interactions through the services consumers already know and trust. We are building products that impress people from the moment they start using them — delightful, magical, and indispensable, through seamless and intuitive design. The team moves quickly, thrives in ambiguity, and focuses on building zero‑to‑one products. We ship fast, care deeply about reliability, security, and craftsmanship, and take ownership from concept to production. We value initiative over process, learning over perfection, and collaboration over hierarchy.
About Us
We are partnering with two seasoned Silicon Valley entrepreneurs and executives who have scaled startups from inception to IPO, led successful exits to Fortune 500 companies, and tripled the valuation of publicly traded firms in record time. The company is backed by a top‑tier Silicon Valley venture capital firm and prominent angels from Anthropic, Google DeepMind, NVIDIA, ARM, and Oracle AI, among others. Although we are technically a seed‑stage company, the amount raised and current valuation place us on par with a typical Series A company. We are a fast‑moving AI startup building ambitious products at the intersection of web applications and modern AI. We are creating a next‑generation personalization experience that seamlessly enhances everyday life — delivering truly magical, meaningful interactions through the services consumers already know and trust. We are building products that impress people from the moment they start using them — delightful, magical, and indispensable, through seamless and intuitive design. The team moves quickly, thrives in ambiguity, and focuses on building zero‑to‑one products. We ship fast, care deeply about reliability, security, and craftsmanship, and take ownership from concept to production. We value initiative over process, learning over perfection, and collaboration over hierarchy.
About The Role
We're looking for people who thrive in ambiguity, move quickly, and love building zero‑to‑one products. We ship fast, cut clean corners, and obsess over reliability, security, and craft. You'll work end‑to‑end — from whiteboard to production — owning services, shaping architecture, and raising the bar for engineering excellence. You'll fit right in if you've worked at an early‑stage company before, or if you've always wanted to experience the intensity and freedom of a startup. Things change daily, and that's part of the fun — you'll wear multiple hats, experiment, and help shape both the product and the culture from the very beginning.
What You'll Do
- Build production-quality products and APIs — design and implement frontends, backend services, and cloud‑native distributed systems with simplicity, performance, scalability, and maintainability; ship pragmatic REST, GraphQL, or gRPC interfaces with versioning, pagination, authnz, schema evolution, and backward compatibility.
- Rapid iteration with ownership and bias for action — iterate quickly with a bias for delivery, take autonomy in decision‑making from day one, and adapt comfortably to a fast‑paced, evolving codebase; own design, implementation, and production outcomes.
- Operate with extreme leverage and build guardrails — aggressively use modern AI tools (e.g., Claude) to accelerate development while maintaining correctness, reproducibility, and maintainability; write rigorous unit and integration tests, maintain meaningful coverage, and produce clear documentation — especially for AI‑assisted code.
- Evolve the AI stack and make principled tradeoffs — prototype and productionize LLM‑dependent features (prompt pipelines, retrievals, structured outputs, evals, guardrails, memory); understand when AI is the right tool versus simpler deterministic solutions, balancing latency, cost, and reliability.
- Distributed systems & cloud architecture — design and operate cloud‑native systems with a solid understanding of scaling, failure modes, state management, consistency models, and graceful degradation.
- Collaborate with product and design — work closely to define roadmap and architecture, turn ambiguous problems into secure, compliant, and high‑quality user experiences, and ensure alignment across teams.
- Mentor and influence teammates — guide through code reviews, design discussions, tech talks, and crisp documentation; promote high engineering standards and team growth.
What Makes You a Great Fit
- Curiosity as a habit — you read release notes, try new runtimes and models, and build weekend prototypes for fun — a lot of your YouTube consumption is hacking and learning new technologies, and you enjoy figuring out what you don't know on your own.
- Self‑driven — you find the problem behind the problem, align stakeholders, and land outcomes without hand‑holding.
- Systems mindset — you think in SLOs, budgets (latency, cost, error), blast radius, and graceful degradation.
- API ergonomics — you care about naming, error design, rate limits, observability, generated SDKs, and docs that don't lie.
- Data foundations — you know when to pick Postgres vs. columnar vs. KV vs. vector; you've shipped schema migrations and zero‑downtime deploys.
- LLM‑practical — you've built RAG or agents in anger; you understand context windows, tokenization, evals, and prompt, tooling hygiene.
- Security instincts — you default to least privilege, tame secrets, and design auth flows that survive real traffic.
Nice to Have
- Hands‑on with vector DBs (e.g., FAISS, HNSW, Milvus, PGVector), embeddings pipelines, and hybrid ranking.
- Can design retrieval layers — embeddings pipelines, vector indexes, hybrid search (BM25 + ANN), chunking, merging strategies, and memory graphs.
- Protocol‑fluent — you actually enjoy HTTP/1.1 vs. HTTP/2/3 quirks, caching semantics, content negotiation, and idempotency.
- Experience with model hosting (self‑hosted inference servers, serverless GPUs, or managed endpoints) and caching, streaming strategies.
- Infra chops — containers, IaC, CI/CD, service meshes, feature flags, canary/blue‑green deploys, cost observability.
- Frontend experience with modern TypeScript frameworks and component systems; accessibility and performance budgets.
- Prior startup experience or meaningful open‑source contributions.
How We Work
- Bias to action — short feedback loops, measured experiments, reversible decisions.
- Quality without ceremony — tests, tracing, and dashboards are table stakes.
- Written culture — design docs, runbooks, and decision logs that future‑you will thank you for.
- Flexible, ownership‑heavy — take on scope that excites (and scares) you a little.
What Success Looks Like (First 90–180 Days)
- You've shipped a user‑visible feature end‑to‑end and made it boringly reliable.
- You've hardened an API (or three) — clear contracts, observability, and error budgets in place.
- You've improved the AI retrieval/memory layer with measurable gains in quality or cost.
- You've leveled up teammates via patterns, docs, or tooling that sticks.
Why Join Us
- Build and scale a transformative product that delights users and has the potential to reach hundreds of millions or even billions of people.
- Be part of the core technical team at an early‑stage, well‑funded AI startup, backed by a top‑tier Silicon Valley VC and prominent angels.
- Work directly with experienced founders who have built and scaled companies to IPOs and multi‑billion‑dollar exits.
- Solve hard, real‑world problems where thoughtful engineering matters more than hype.
- High ownership, high impact, and rapid growth opportunities — a rare chance to join at the earliest stage and make a significant impact.
- Competitive compensation, meaningful equity, benefits, and strong long‑term upside.
Candidate Requirements
- 10–15 years of professional software engineering experience.
- Startup experience strongly preferred over candidates with only big‑company backgrounds.
- Must be hands‑on — this is not a fit for managers who are out of touch with the code.
- Must currently reside in the SF Bay Area; relocation is not an option for this role.
- Must be willing to work from the Palo Alto office 5 days per week — this is an early‑stage, in‑person, collaborative environment.
- Reasonably long tenure at prior companies preferred (not a pattern of 1–2 year stints), unless there is a legitimate explanation.
- Strong cultural fit — including willingness to meet in person for initial interviews.
- Genuinely ready for a 0‑to‑1 opportunity, with the experience to back it up.
- Visa sponsorship not preferred, though exceptions may be made for an exceptional (\"rockstar\") candidate.
- Exceptional work ethic and a mindset of finding ways to make the impossible possible.
Compensation & Logistics
- Base salary: $200,000 – $300,000, commensurate