Role Details
Title: Software Engineer - Growth Infrastructure
Focus on building infrastructure for growth team, handling expert marketplace, onboarding, and automations
Candidate Requirements
Ideal candidates from marketplace companies or competitors
Looking for general infrastructure engineers, not specifically growth engineers
Company Context
Company experiencing high growth, requiring new infrastructure
Flexibility in role assignment based on candidate fit and interest
Compensation and Logistics
Base salary range: $250K - $300K, plus competitive equity
Work arrangement not specified; assumed similar to other roles
Interview Process
Includes intro call, behavioral round, take-home assignment, and system design
Paid workshops for trials: $400/day
Timeline and Urgency
Goal to hire 6 Growth Infra engineers by end of year
Urgency due to high company growth targets
Pain Points
Struggling with bottlenecks in hiring high-quality candidates
Need infrastructure to support rapid scaling and expert onboarding
Ideal Candidate Profile
Experience in marketplace companies or infrastructure engineering
Adaptable and willing to pivot across different roles based on company needs
Requirements
By tier
By category
Calibrate a candidate in Parabot. to see how well they fit the requirement Dealbreaker
Work experience
Scaled core infra at an S-tier VC-backed startup, reputable trading firm, or founding engineer at company that has raised $2.5M+. If big tech only, must have CS degree from top-10 CS program (e.g., Berkeley, CMU).
Updated
Hard skills
Proficient in Node.js/Python, Kubernetes
Updated
Soft skills
Experience building something end-to-end with a bias towards ownership
Updated
Baseline
Seniority
2 - 5 years of experience as a fullstack SWE
Education
Degree from top-30 school (US/CA/EUR only).
Updated
Miscellaneous
Willing to work 5 days a week (M-F) in our FiDi (SF) office. Flexible working hours (e.g., can come in whenever preferred).
Updated
Nice-to-have
Work experience
Marketplace or growth infra experience at a high-growth startup. Growth engineer at a data company is the ideal profile
Updated
Any new grads (or 1 YOE) must have multiple S-tier internships (Stripe or better)
Updated
Experience at human data AI company (e.g., Surge AI, Snorkel AI, Micro1, Mercor). We will pay as much as needed for this profile.
Updated
Hard skills
Kafka, Redis, Elasticsearch
Updated
Traits to avoid
Undergrad not from US/CA/EUR (NO EXCEPTIONS!)
Updated
Contractors or consultants
Updated
No new grads who aren't top .1% of new grads (multiple S-tier internships like Stripe or better)
Updated
Currently works at OpenAI
Updated
No candidates coming from Amazon unless Amazon Mechanical Turk.
Updated
International students coming from master's programs
Updated
Non-YC founders or founders that have not raised at least $2.5M
Updated
About this role
We are looking for a Software Engineer – Growth Infrastructure with 2+ years of experience to build the core infrastructure that powers expert acquisition, onboarding, and matching at scale. This is not a traditional growth engineering role – you'll be building the platform and tooling that enables the growth team to hire, assess, interview, onboard, and retain domain experts across projects. You'll own end-to-end systems from outreach tooling and AI-powered interviewing to automated expert-to-project matching. This role offers significant autonomy and the opportunity to eventually build machine learning–driven recommendation systems that predict which expert profiles are needed before a project even launches.
What you will be doing
Building and owning the expert marketplace infrastructure – covering outreach, interviewing (including an AI interviewer), assessments, and onboarding tooling
Developing the hiring platform where experts are onboarded, managed, and dispatched to projects based on fit and availability
Creating automations and internal tools that replace manual workflows for the growth team – dramatically increasing operational throughput
Partnering directly with growth associates to identify bottlenecks, instrument the funnel, and ship high-leverage improvements quickly
Eventually building ML-driven recommendation systems that predict expert needs for new projects and automate the staffing pipeline
Role details
Salary
$250K - $300K (OTE: $300K - $400K)
On-site work policy
5 days a week (M-F) in our FiDi (SF) office and half-day or remote on Sunday.
Full-time position
Location
San Francisco, CA
Equity
Competitive Equity
Visa sponsorship details
Open to visa transfers (e.g. OPT, H1B transfers)
Hiring Count
Looking to hire 4 - 5 candidates for this role
Tech stack
TypeScript/JavaScript, Next.jS, React, Node.js, Python, Kubernetes, Kafka, Redis, Elasticsearch, Cloud Platforms: AWS, GCP
What to ask candidates
Describe the infra you've scaled with Node/Python + Kubernetes, and the company stage at the time.
Can the candidate be on-site? If not, is the candidate willing to relocate?
What is their salary expectation?
How actively is this candidate exploring new opportunities?
Interview process
Hear the hiring manager walk through the interview proIdeal candidates & backgrounds
Ideal companies & backgrounds
Updated Oct 8, 2026
Here are a list of companies AfterQuery likes to see candidates with past work experience from. You can also use these companies and adjacent companies as a place to start sourcing candidates.
High-growth AI/ML/Data Startups (Series A-B, Tier 1 Investors)
Listen Labs
Listen Labs
Fireworks AI
Fireworks AI
Genspark
GensparkRejected candidate feedback
Enforce education/region – Only consider candidates with US/CA/EUR undergrad (or top-10 if from big tech) to meet our rigorous academic benchmark.
Marketplace/growth infra focus – Prioritize candidates with direct end-to-end ownership in marketplace or growth infrastructure, particularly from S-tier startups or human data AI companies.
Tech stack alignment – Ensure clear hands-on experience in Node.js/Python and Kubernetes; verify that their infra role includes building scalable, production-grade systems.
Avoid non-core backgrounds – Do not submit Amazon candidates (unless Mechanical Turk) or those from contract roles/consultants lacking deep ownership in similar roles.
