About this template
The USA Tech template is an American tech CV in JetBrains Mono for titles and Inter for body, graphite palette and dedicated stack section. Open-source links and project repositories occupy their own lines so a hiring manager can click directly through. Suits English-speaking candidates targeting FAANG, late-stage scale-ups and YC alumni.
Who is it for?
It fits software engineers, SRE, ML and data engineers, infra and platform profiles applying to FAANG (Meta, Apple, Amazon, Netflix, Google, Microsoft), late-stage scale-ups (Stripe, Databricks, Snowflake, Anthropic, OpenAI, xAI) and YC alumni (Coinbase, Airbnb, DoorDash, Instacart, Brex, Ramp) in the United States. The stack-first structure speaks to engineering managers who scan for specific languages, frameworks and infra primitives before reading prose.
How to use it
One page strictly (two pages tolerated for Staff/Principal engineers with 10+ years). In the header, a line with links: GitHub (github.com/username), portfolio if applicable (username.dev), research paper if applicable (arxiv ID). A Technical Stack section at the top lists by category: Languages (Go, Rust, Python, TypeScript), Cloud (AWS, GCP — specific services), Infra (Kubernetes, Terraform, Pulumi), Observability (Datadog, Prometheus, Grafana), Databases (Postgres, Redis, ClickHouse). Reverse chronology on Experience with quantified bullets: « Reduced p99 latency from 850ms to 90ms by introducing Cassandra read-through cache (Q3 2023) ». For open-source contributions, mention major projects with direct links.
Frequently asked questions
Should I really list the stack first?
Yes for FAANG, late-stage scale-ups and YC. Engineering managers spend 6-10 seconds on a junior CV and 15-20 seconds on a senior CV, scanning the stack first to validate technical fit before reading experience. For a Stripe Staff Engineer, seeing Rust + Go + Postgres + Kubernetes in the first section accelerates the recruiter decision.
How many open-source projects to list?
Three to five maximum, with direct links and impact signals (GitHub stars, npm/PyPI downloads, academic citations if paper-backed). Favour projects YOU maintain or actively contribute to (top-10 contributor) over abandoned forks. For contributions to large projects (Linux kernel, Kubernetes, Rust compiler), specify the scope (« kernel network subsystem, 30+ accepted patches »).
How to position non-US experience for US FAANG?
Specify size (headcount and revenue) and sector in North American terms: « Doctolib (Series F, $2bn valuation, healthcare SaaS) » or « Mistral AI (Series A, $2bn valuation, generative AI foundation model) ». For the stack, keep international technical names — no need to translate. Mention technical conferences where you have spoken (FOSDEM, KubeCon EU, PyCon FR) — valued signal.
