AfterQuery — Senior Software Engineer, Infrastructure and Platform

Type: Full-time | On-site | San Francisco, CA Compensation: $180,000–$220,000 + Competitive equity (4-year vest) (band carried from original posting — likely low for a senior 5+ req; confirm) Hiring count: 4 Visa sponsorship: O-1, OPT Reports to: Interviews run by Alec (Initial Screen) and an engineer (Second Round); works directly with the founding team

About AfterQuery

AfterQuery is a research lab investigating the boundaries and capabilities of artificial intelligence through novel datasets and experimentation. Its customers are the frontier AI labs — every major foundation-model lab is a client. Backed by Y Combinator, BoxGroup, ex-partners from Lightspeed and Index Ventures, and senior leadership at Google DeepMind and Meta GenAI; one of the fastest-growing companies in its YC batch. 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 Lab (SAIL).

Founded: 2025 | Team size: 11–50 | Stage: Series A (company card) / "seed-stage" per outreach — confirm Industry: AI research / data infrastructure for frontier labs Website: afterquery.com Office: San Francisco, CA

Why Candidates Should Join

• Foundational ownership: Architect and build the core infrastructure that many other engineers and researchers depend on — broad ownership from day one.
• Frontier impact: The platforms you build power the data generation, evaluation, and agentic systems used to train frontier AI models, with every major foundation-model lab as a customer.
• Architecture-defining seat: Work directly with the founding team to define system architecture and set engineering best practices for the next generation of AI development.
• Backing & trajectory: YC-backed and one of the fastest-growing in its batch, elite investors and founding team, competitive salary + equity (4-year vest), daily lunch & dinner, gym, 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 Senior Software Engineer, Infrastructure and Platform, you'll design and build the core infrastructure powering AfterQuery's data generation, evaluation, and agentic systems — the shared platforms that let engineers and research teams run large-scale human-in-the-loop workflows, evaluation harnesses, and automated data pipelines used to train frontier models. Highly technical, broad ownership: you architect foundational systems others depend on, ensuring scale, reliability, and extremely high throughput.

What You'll Be Doing

• Architect and develop the shared infrastructure powering data generation platforms, human-in-the-loop systems, and evaluation pipelines
• Build systems capable of processing large-scale datasets and high-throughput workloads with strong reliability guarantees
• Create reusable infrastructure and APIs that enable product engineers and researchers to build quickly and reliably on top of core systems
• Design systems with strong observability, monitoring, and fault tolerance to support production workloads at scale
• Help define long-term system architecture across data pipelines, compute infrastructure, task orchestration, and storage systems
• Work closely with engineers and researchers to support new AI experimentation workflows and platform capabilities
• Define standards for system design, deployment, reliability, and infrastructure operations

Tech stack: Python, JavaScript (Node.js / Next.js) · GCP / AWS · message queues / event-driven (Kafka, RabbitMQ, Pub/Sub) · high-throughput async data pipelines · (original posting also cited Go, Redis, Elasticsearch, Kubernetes)

Requirements

• 5+ years of experience building production distributed systems or platform infrastructure
• Proficiency in Python and/or JavaScript (Node.js/Next.js) or similar backend technologies
• Experience designing and operating systems in cloud environments (GCP or AWS)
• Experience with message queues and event-driven systems (Kafka, RabbitMQ, Pub/Sub, or equivalent)
• Experience working with high-throughput data pipelines and asynchronous processing systems
• Strong understanding of system scalability, performance, and reliability
• Experience owning systems running in production environments at scale
• Background at a top-tier startup or FAANG-equivalent, this is a strong signal of fit

Green Flags

• Experience building internal developer platforms or shared infrastructure
• Experience supporting large-scale data processing pipelines
• Experience with AI infrastructure, LLM evaluation systems, or ML pipelines
• Experience working at high-growth startups or scaling early infrastructure
• Experience designing human-in-the-loop or workflow orchestration systems

Red Flags

• Only mid-level or IC contributor experience with no architectural ownership
• Background exclusively at large legacy enterprises or slow-moving companies
• Has never owned a production system end-to-end
• No cloud infrastructure depth in GCP or AWS
• No experience with high-throughput or distributed systems
• Under 5 years of experience
• Undergraduate degree from the U.S., Canada, or the U.K.

Role Details

Submission Form Questions (Contrario Required Candidate Q&A)

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) Stage 3 — Second Round (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

Per Requirements/Green Flags: top-tier startups or FAANG-equivalent; teams where the candidate architected and owned production infrastructure at scale, built internal developer platforms, or scaled early infrastructure at high-growth startups.

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

Rejected Candidate Feedback

Activity log shows one candidate rejected by the company ~12 hours ago; no feedback text was available on the page. None captured.