Asks for

The ad says“AI-native by default. You use AI coding and reasoning tools as a normal part of how you design, prototype, review, and write — and you have opinions, from experience, about where they accelerate engineering work and where they don't yet.”
The ad says“Experience designing public APIs and SDKs at scale, including versioning, backward compatibility, and multi-surface consistency.”
The ad says“Deep expertise in distributed systems and high-throughput, low-latency backend architecture (Go or similar systems language; Kubernetes/AWS; event-driven and data-intensive systems). Fluency across adjacent layers — client SDKs, data pipelines, ML serving — is a strong plus.”
The ad says“Deep expertise in distributed systems and high-throughput, low-latency backend architecture (Go or similar systems language; Kubernetes/AWS; event-driven and data-intensive systems). Fluency across adjacent layers — client SDKs, data pipelines, ML serving — is a strong plus.”
The ad says“Deep expertise in distributed systems and high-throughput, low-latency backend architecture (Go or similar systems language; Kubernetes/AWS; event-driven and data-intensive systems). Fluency across adjacent layers — client SDKs, data pipelines, ML serving — is a strong plus.”
The ad says“Deep expertise in distributed systems and high-throughput, low-latency backend architecture (Go or similar systems language; Kubernetes/AWS; event-driven and data-intensive systems). Fluency across adjacent layers — client SDKs, data pipelines, ML serving — is a strong plus.”
The ad says“Deep expertise in distributed systems and high-throughput, low-latency backend architecture (Go or similar systems language; Kubernetes/AWS; event-driven and data-intensive systems). Fluency across adjacent layers — client SDKs, data pipelines, ML serving — is a strong plus.”
The ad says“Experience designing public APIs and SDKs at scale, including versioning, backward compatibility, and multi-surface consistency.”
The ad says“10+ years of software engineering experience, including 3+ years operating as an Architect for a 100+ Engineering org — you have owned architecture for a platform, not just a service.”
The ad says“Exceptional written communication. You make complex decisions legible to engineers and executives alike, and you default to async, documented decision-making.”

Fingerprint empowers enterprises to detect and stop online fraud with the world’s most accurate device intelligence. We lead our industry with bleeding-edge identification capabilities and work on turning new ideas and discoveries in the fraud detection space into reality. Our customers range from innovative startups to leading enterprise companies, including Plaid, Dropbox, and Booking.com.

Fingerprint is a globally dispersed, 100% remote company. We were named on on the 2026 Forbes Best Startup Employers list and ranked #803 on the 2026 Inc. 5000 list of America’s fastest-growing private companies.

We have raised $77M and are backed by Craft Ventures (Tesla, Facebook, Airbnb ), Nexus Venture Partners ( Postman, Apollo.io, MinIO, Druva) and Uncorrelated Ventures ( Redis, Rollbar, Gradle).

About the role

You will be Fingerprint's first dedicated Architect. You will lead cross-cutting architecture — how our systems fit together and where they need to go — working alongside the Staff and Lead engineers who already shape them, without direct reports. The mandate has three parts. First, go deep: build the end-to-end picture nobody currently has time to hold, identify where the platform will strain as we scale, and set the direction to address it. Second, raise the bar: strengthen and extend our design review, API, service, and reliability practices so eight engineering groups can move fast without stepping on each other. Third, make it durable: give cross-cutting architecture work consistent cadence, a durable decision record, and follow-through, so strong individual judgment compounds into platform-level outcomes.

You report directly to the VP of Engineering. That placement is deliberate — you need neutrality across groups so the standards you set with teams are adopted everywhere.

What you'll do

Own the end-to-end architecture

Build and maintain the end-to-end architecture picture — data flows, service boundaries, ownership seams — and keep it current as the org changes.
Identify systemic scaling, reliability, and cost risks across the pipeline (ingestion, identification, signals, delivery) and drive architectural changes to address them before they become incidents.
Set direction for API design and service patterns across REST, SDK, and MCP surfaces so customers see one coherent platform.
Shape the roadmap for foundational initiatives (e.g., cell architecture, multi-region readiness, rate limiting, feature flag infrastructure) and lead the hardest designs yourself.

Lead cross-cutting architecture

Serve as full-time technical lead across the engineering org: set the agenda, drive decisions to closure, own the decision record, and follow through on adoption across teams.
Partner with Engineering leadership and the Staff/Lead engineers across teams to prioritize cross-cutting work and connect it to team roadmaps.
Mentor Staff-level engineers on system design, technical writing, and influence — raise the bar for what "Staff" means at Fingerprint.

Strengthen and extend best practices

Build on the design review practices we already have (RFCs, cross-team design reviews) and make them more consistent, lighter-weight, and more useful, so teams choose to use them.
Codify and extend standards for observability, quality, security-by-design, and API evolution/versioning, working with Cloud Platform, Security, and product teams.
Review and sign off on critical designs; teach through review rather than gatekeeping.

Set us up for scale

Translate business trajectory (Tier 1 enterprise customers, new product launches, AI/MCP workflows) into a multi-quarter technical strategy and sequence the work.
Advise Engineering leadership and executive team on build/buy, platform investment, and technical risk in plain language.
Lead AI adoption in engineering practice: set norms for AI-assisted design, coding, and review across teams, and shape our architecture and documentation so AI agents can work in our systems as effectively as engineers do.
Stay hands-on: prototype, write reference implementations and documentation, and dig into production when the problem demands it.

What we're looking for

10+ years of software engineering experience, including 3+ years operating as an Architect for a 100+ Engineering org — you have owned architecture for a platform, not just a service.
Track record of leading through influence: you have led senior engineers you didn't manage, run design review or architecture forums that people actually used, and driven adoption of standards across an org.
Deep expertise in distributed systems and high-throughput, low-latency backend architecture (Go or similar systems language; Kubernetes/AWS; event-driven and data-intensive systems). Fluency across adjacent layers — client SDKs, data pipelines, ML serving — is a strong plus.
Experience designing public APIs and SDKs at scale, including versioning, backward compatibility, and multi-surface consistency.
Demonstrated ability to anticipate systemic risk and act on it — you can point to failures you prevented, not just ones you fixed.
Exceptional written communication. You make complex decisions legible to engineers and executives alike, and you default to async, documented decision-making.
AI-native by default. You use AI coding and reasoning tools as a normal part of how you design, prototype, review, and write — and you have opinions, from experience, about where they accelerate engineering work and where they don't yet.
Architect for an AI-assisted org. You think about how codebases, documentation, service boundaries, and APIs should be shaped so that both humans and AI agents can work in them safely — legible structure, strong contracts, automated verification.
Pragmatism over purity. You balance long-term architecture with delivery pressure and know when "good enough" is the right call.
Comfortable being the first: you have stepped into a dedicated role where the work was previously shared across a group, earned the trust of the people already doing it, and made them more effective rather than displacing them.

Nice to have

Experience in fraud detection, identity, device intelligence, or other adversarial domains.
Multi-region / cell-based architecture experience.
Experience with MCP, LLM tool integrations, or agent-facing API design.
Familiarity with ClickHouse, Kafka, or similar high-volume data infrastructure.

Compensation & Transparency

For US-based employees, the cash compensation range for this role is $177,000 – $240,000. We set standard ranges for all US roles based on function, level, and geographic location, benchmarked against similar stage growth companies. To comply with local legislation and provide greater transparency, we share salary ranges on all job postings. However, these ranges are specific to the hiring location and may differ within or outside the US. Offers vary depending on, but not limited to, relevant experience, education, certifications/licenses, skills, training, and market conditions.

Due to regulatory and security reasons, there's a small number of countries where we cannot have Fingerprint teammates based. Additionally, because Fingerprint is an all-remote company and people can join our workforce from almost any country, we do not sponsor visas. Fingerprint teammates need to be authorized to work from their home location.

We are dedicated to creating an inclusive work environment for everyone. We embrace and celebrate the unique experiences, perspectives and cultural backgrounds that each employee brings to our workplace. Fingerprint strives to foster an environment where our employees feel respected, valued and empowered, and our team members are at the forefront in helping us promote and sustain an inclusive workplace. We highly encourage people from underrepresented groups in tech to apply.

If you are applying as a resident of California, please read our CCPA notice here.

If you are applying as a resident of the EU, please read our GDPR notice here.

We have noticed a rise in recruiting impersonations across the industry, where scammers attempt to access candidates' personal and financial information through fake interviews and offers. All Fingerprint recruiting email communications will always come from the @fingerprint.com domain. Any outreach claiming to be from Fingerprint via other sources should be ignored.*

Due to regulatory and security reasons, there’s a small number of countries where we cannot have Fingerprint teammates based. Additionally, because Fingerprint is an all-remote company and people can join our workforce from almost any country, we do not sponsor visas. Fingerprint teammates need to be authorized to work from their home location.