# AfterQuery — Software Engineer, Platform / Applied AI (Full-Stack) Type: Full-time | On-site | San Francisco, CA Compensation: $180,000–$220,000 + Competitive equity (4-year vest) Hiring count: 4 Visa sponsorship: O-1, OPT Reports to: Interviews run by Alec (Initial Screen) and an engineer (Second Round); founding-team reporting line — confirm ## About AfterQuery AfterQuery is a research lab investigating the boundaries and capabilities of AI through novel datasets and experimentation. Its customers are the foundation-model labs — it serves the frontier AI labs. Backed by top investors including Y Combinator and BoxGroup, ex-partners from Lightspeed and Index Ventures, and senior leadership at Google DeepMind and Meta GenAI. The founding team brings backgrounds from Jane Street, Meta, Citadel Securities, Google, Goldman Sachs, Morgan Stanley, Silver Lake, Berkeley AI Research (BAIR), and the Stanford AI Laboratory (SAIL). Reported $25M+ annualized revenue and one of the fastest-growing companies in its YC batch. Founded: 2025 | Team size: 11–50 | Stage: Series A (company card) — outreach describes it as "seed-stage"; confirm Industry: AI research / data infrastructure for frontier labs Website: afterquery.com Office: San Francisco, CA ## Why Candidates Should Join - Founding ownership: One of the first hires; own entire projects end-to-end and define/own the data infrastructure from day one, with immediate visible impact. - Frontier impact: Build the data infrastructure shaping frontier-model development, with the frontier AI labs as direct customers. - Trajectory & backing: One of the fastest-growing companies in its YC batch, $25M+ annualized revenue, elite founding team and investors, with a path to lead and grow an engineering team as they scale. - Comp & perks: Competitive salary + equity (4-year vest), daily lunch & dinner covered, free gym membership, health insurance. ## Intake Call Summary The role page provides an intake video only — no transcript was captured. Summary unavailable; review the intake video on the Contrario page before finalizing scoring nuances. ## The Role As a core/founding engineer, you'll build the data infrastructure shaping frontier-model development, owning projects end-to-end across frontend, backend, and infrastructure. ### What You'll Be Doing - Build and scale complex data-capture workflows across web (Next.js) and desktop (Python) - Architect and optimize high-throughput data pipelines under heavy load - Collaborate with the founding team to define product strategy and ship features fast - Set engineering best practices and lay the groundwork for future team growth Tech stack: Next.js / JavaScript / TypeScript, Python, Go · GCP/AWS (serverless, cloud functions) · Kubernetes · Redis · Elasticsearch · Kafka / RabbitMQ · NoSQL · APIs ### Required Qualifications (role body) - Proficiency in JavaScript (Next.js) and Python, with demonstrated experience building full-stack web applications - Experience with serverless architecture and cloud functions for heavy data processing (GCP/AWS) - Storage, caching & search: hands-on with Redis (caching), Elasticsearch (indexing), and message queues (Kafka/RabbitMQ) to build scalable, low-latency pipelines - Any background in AI research, LLM evaluation, or human-in-the-loop systems - Experience getting your ideas into production (founder experience preferred) ## Requirements - Must come from a top university (US/Canadian/UK), top quant firm, or have founding engineer experience. - Strong coding fundamentals in Node.js / TypeScript, Python and/or Go. - Deep understanding of distributed systems, scalability challenges, and system design. - Familiarity with cloud platforms (GCP/AWS), Kubernetes, APIs, NoSQL databases. - Ability to reason about trade-offs and balance speed vs reliability. - Strong communication skills and a bias toward ownership, curiosity, and delivering simple solutions to complex problems. - Bonus: Experience with RL environments, agentic systems, or human-in-the-loop workflows. ## Green Flags - GitHub is filled green, a builder at heart - Experience working with AI-agents and RL environments - Preferably someone who has worked at a top tier quant firm or as a founding eng (or multiple internships) at high-growth startups - Has trialed or succeeded in past fast-paced startup roles with strong references. - Works autonomously, yet collaboratively, and doesn't burn out under heavy load. - We want a SWE that can pretty much work banker hours - Ex-founders where their product is pretty sophisticated and complex ## Red Flags - Isn't proactive - Can't articulate why they want to pivot into AI ops or join a startup now. - Worked cushy tech jobs (FAANG PM, etc.) and may not be used to intense work environments. - Wants work life balance ## Role Details Salary$180,000–$220,000EquityCompetitive (4-year vest)Experience0–4 yearsOn-site policyOn-site, San FranciscoVisa sponsorshipO-1, OPTEmployment typeFull-timeLocationSan Francisco, CAOpenings4 ## Submission Form Questions (Contrario Required Candidate Q&A) These are asked on the Contrario submission form (not call screening): 1. LinkedIn Profile 2. Are you legally authorized to work in the country where you are applying? 3. Will you now or in the future require visa sponsorship for employment? No separate Screening Questions set was provided on the role page. ## Interview Process Stage 1 — Pending Approval — Contrario submission approval. Stage 2 — Initial Screen (Alec) — First screen. Stage 3 — Second Round (Engineer) — Technical round with an engineer. Stage 4 — Take Home Stage 5 — Post Take Home Stage 6 — Work Trial Stage 7 — References Stage 8 — Offer Extended Stage 9 — Candidate Hired — Candidate accepts and starts. ## Ideal Companies & Backgrounds No dedicated "Ideal Companies" section on the role page. Per Requirements/Green Flags, the target background is: top universities (US/Canadian/UK), top-tier quant firms, or founding-engineer / multiple-internship experience at high-growth startups; ex-founders of sophisticated products. ## Ideal Candidate Profiles For reference only — DO NOT CONTACT (per Contrario). LinkedIn buttons were present on the page but no URLs were captured in the HTML. - Liang (David) Liu - Frithiof Ekström - Stephanie Su - Ricky Raup - Taha B. - Serena (Qianhan) H. - Kush Bhagat - Kyle T. - Naren Duggirala - Ryan Henry