Full Stack AI Engineer- CA

Recruiting Partner Notes- Not to be shared with candidatesPlease review the following requirements carefully before submitting a candidate.This is a highly selective, fully onsite Full Stack AI Engineer search for an early-stage startup in San Francisco. The client is specifically looking for engineers with genuine zero-to-one startup experience.Candidate RequirementsCandidate must currently live within a reasonable commuting distance of San Francisco and be willing to work onsite five days per week.Remote, hybrid, and relocation-dependent candidates will not be considered.Candidate must have prior experience working at an early-stage startup.Candidate must have personally helped build and launch a product from zero to one.Please do not submit candidates whose experience is exclusively with FAANG, large technology companies, consulting firms, or mature enterprise environments.FAANG experience is acceptable when combined with meaningful early-stage startup experience.Candidate must still be hands-on and actively writing production code. This is not an engineering management or architecture-only position.Candidate should have strong full-stack experience across frontend, backend, databases, APIs, cloud infrastructure, and production deployments.Candidate must have practical experience building AI-powered products. API experimentation, personal projects, coursework, or basic chatbot integrations alone will not qualify.Strong candidates will have experience with AI agents, LLM integrations, RAG, model tool calling, multimodal AI, voice AI, evaluations, or real-time AI systems.Resume and LinkedIn VerificationBefore submitting, carefully compare the candidate's resume and LinkedIn profile.Employment dates, job titles, company names, education, and career history should be consistent.Please resolve any discrepancies before submitting the candidate.Do not submit candidates with unexplained overlapping employment, conflicting dates, inflated titles, or companies that cannot be reasonably verified.Confirm that the candidate personally performed the work being presented and is not overstating team accomplishments as individual contributions.A current LinkedIn profile must be included with every submission.Please discuss any employment gaps, short tenures, or major career transitions with the candidate before submitting.Required Candidate ScreeningPlease speak directly with the candidate before submitting. Do not submit candidates based only on a resume review, email exchange, or LinkedIn message.Your candidate summary should address:Current location and ability to work onsite five days per weekCurrent compensation and compensation expectationsWork authorization and any present or future sponsorship requirementsEarly-stage startup experienceSpecific zero-to-one product the candidate helped buildThe candidate's personal technical contribution to that productProduction AI experience and the AI technologies usedCurrent level of hands-on codingReason for leaving each recent positionInterest in joining a fast-moving, early-stage startupInterview availability and potential start dateSubmission QualityPlease submit only candidates who clearly meet the core requirements. Quality is significantly more important than volume.Do not submit candidates who have not reviewed the onsite requirement.Do not submit candidates who are applying broadly without a specific interest in this opportunity.Do not submit candidates who are primarily seeking management, remote work, or a highly structured corporate environment.Do not submit candidates who need extensive convincing regarding compensation, location, startup risk, or onsite expectations.Confirm the candidate has authorized you to represent them for this specific opportunity.Check Top Echelon for duplicate ownership before submitting.Include a concise candidate write-up explaining why the individual is a strong match. A resume without screening notes will not be considered a complete submission.Interview ReadinessCandidates should be prepared to discuss:A product they personally built from zero to oneTechnical and architectural decisions they madeTradeoffs between speed, scalability, cost, and qualityAI systems they have deployed into productionHow they measured and improved AI output qualityA situation where requirements were unclear and they had to create the solutionTheir individual contribution versus the contribution of the broader teamWhy they want to work onsite at an early-stage San Francisco startupCandidates may be asked to complete a technical assessment, live coding exercise, architecture discussion, or product-building exercise.JOB DESCRIPTION:We are partnering with an early-stage, cutting-edge AI startup in San Francisco to hire a Full Stack AI Engineer with strong zero-to-one product-building experience.This is a fully onsite position. Candidates must currently live in the San Francisco Bay Area and be able to work from the company's San Francisco office five days per week. Please do not apply if you are seeking remote or hybrid work.About the RoleOur client is looking for a highly hands-on engineer who can help build and launch AI-native products from the ground up. You will work closely with the founders to turn ideas into production-ready applications and help shape the company's technical foundation.The right candidate is comfortable working across frontend, backend, infrastructure, and AI systems. You should enjoy fast-moving startup environments, unclear requirements, rapid iteration, and taking full ownership of what you build.ResponsibilitiesBuild, test, launch, and improve full-stack products from zero to oneDevelop modern frontend applications using React, Next.js, or similar technologiesBuild backend services, APIs, databases, and integrationsCreate AI-powered features using large language models and multimodal modelsBuild AI agents that can use tools, complete workflows, and interact with external systemsDevelop retrieval-augmented generation, embeddings, vector search, and knowledge systemsIntegrate voice AI, speech-to-text, text-to-speech, or real-time conversational systemsImplement model routing, structured outputs, tool calling, and human approval workflowsBuild evaluation, monitoring, and testing systems for AI performanceImprove application speed, reliability, scalability, security, and AI inference costsWork directly with founders, users, and product stakeholdersHelp make product, architecture, and technology decisionsQualifications4 or more years of professional software engineering experienceProven experience building and launching a product from zero to oneStrong experience across both frontend and backend developmentExperience working at an early-stage startupStrong skills in TypeScript, JavaScript, React, and Next.jsBackend experience with Node.js, Python, FastAPI, Go, or similar technologiesExperience with PostgreSQL, APIs, cloud infrastructure, and production deploymentsHands-on experience integrating large language models into production applicationsExperience with AI agents, RAG, tool calling, embeddings, or multimodal AIStrong product judgment and the ability to work with limited directionAbility to move quickly while maintaining high engineering standardsPreferred ExperienceOpenAI, Anthropic, Gemini, or open-source AI modelsModel Context Protocol and agent orchestration frameworksLangGraph, LlamaIndex, Vercel AI SDK, or similar toolsVector databases such as Pinecone, Qdrant, Weaviate, or pgvectorVoice AI, WebSockets, WebRTC, or real-time streaming systemsAI evaluations, observability, prompt injection protection, and model securityDocker, AWS, Google Cloud, Azure, or serverless infrastructureExperience as an early, founding, or first engineering hireIdeal CandidateYou are a builder who prefers creating new products over maintaining mature systems. You are comfortable wearing multiple hats, making decisions quickly, and turning incomplete ideas into products that customers can use.You understand that strong AI products require more than connecting to a model API. You know how to build dependable workflows, evaluate output quality, manage latency and cost, and create safeguards around AI-generated actions.Location RequirementThis role is onsite in San Francisco five days per week.Candidates must already live within a reasonable commuting distance of San Francisco. Remote, hybrid, relocation-dependent, and out-of-area candidates will not be considered.