About Blinq
Blinq is the AI contacts app for people who meet people.
We're on a mission to unlock the world's relationship potential. So much of what's possible in the world is locked inside relationships that never quite happen. A missed conversation, a forgotten follow-up, the right person at the wrong time. We're building so those chances aren't left to chance.
What started as the world's #1 digital business card is now used by 4 million professionals and at 93% of the Fortune 500. We've raised $45m+ from Blackbird, Square Peg, HubSpot Ventures, and Touring Capital.
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Our engineering team is the engine behind Blinq’s success. We’re building tools that make sharing who you are instant and human. Every line of code, every release, and every experiment is focused on driving meaningful impact. If you thrive on solving complex, high-impact problems with a tight-knit team, you’ll feel right at home here.
Role & Impact
As a Senior Platform Engineer at Blinq, your customers are our engineers. You'll own the systems, pipelines and tooling that sit between an idea and a shipped feature, and make that path faster, safer and more enjoyable across every stack we build on: iOS, Android, and our TypeScript web and backend services on Google Cloud.
The role blends two things. Part of your time sits alongside our SRE team: making it easy for every engineer to instrument their own code and understand how it behaves in production, through the patterns, tooling and AI assistance that make good observability the default rather than a specialist skill. The larger part is developer experience: shortening CI/CD, building internal tools, paving the roads engineers use every day, and hardening how we detect and manage vulnerabilities. Security runs through all of it: the platform you build is how secure defaults reach every engineer, so the easy path and the safe path should be the same path.
Underneath all of it is AI. Blinq is an AI-native company and we expect the same of our engineering practice. You'll use AI tools heavily in your own work, and you'll be the person who works out where AI belongs in the developer workflow, builds the environments and guardrails that let coding agents do useful work, and brings the rest of the team along. Our ambition is a loop where writing, testing, building and distributing software can increasingly run end to end with AI in it, and the platform you build is what makes that possible.
This is not a back-office role. You'll spend a lot of your week with other engineers and with QA: pairing on their problems, sitting in their retros, watching where they lose time, and shipping fixes that they notice. The measure of success is whether engineers at Blinq say the platform made them faster.
What You'll Do
Observability and reliability
- Work with our SRE team to make observability self-serve: build the patterns, libraries, templates and AI-assisted workflows that let engineers instrument their own services and apps well, across RUM, APM, metrics and logging in Datadog.
- Turn what we learn from incidents and operational health into platform improvements that engineers benefit from without having to think about it.
Developer experience
- Make CI/CD meaningfully faster and more reliable across web, backend, iOS and Android: caching, parallelism, flaky-test detection, and release automation for the mobile stores.
- Make it fast and easy to spin up, test and share isolated environments for work in progress, across web, backend and mobile, for people and for automation.
- Partner with QA to make automated testing a natural part of how engineers work, with fast and trustworthy signal for engineers and agents alike.
- Own the inner loop: local and cloud development environments, seed data, scaffolding and templates, so a new engineer or a coding agent can be productive on day one.
- Build internal tools that remove toil, and retire ones that no longer earn their keep.
- Pair with product engineers on the problems that slow them down, and treat their feedback as your roadmap.
AI enablement
- Set the standard for how engineers at Blinq use AI tools, from your own workflows to the environments, context and guardrails that make agents effective and safe in our codebase.
- Identify where AI genuinely improves developer efficiency, roll it out with the team, and be equally clear about where it doesn't.
Infrastructure and security
- Evolve our Google Cloud infrastructure through infrastructure as code (IaC), with an eye on cost, access hygiene and simplicity.
- Streamline vulnerability detection and management across dependencies, images and infrastructure, so fixing security issues is fast and low-friction rather than a quarterly scramble.
- Bring a security-first lens to everything you ship, from CI credentials and ephemeral environments to the access agents have in our codebase, and help other engineers do the same.
What You'll Bring
- Around 5 or more years in platform, developer productivity, DevOps, SRE or infrastructure roles, with a track record of making other engineers faster.
- Concrete examples of CI/CD pipelines you've made significantly faster or more reliable, ideally including mobile (iOS and/or Android) builds and releases.
- Experience with ephemeral environments and end-to-end test automation, and a view on how the two fit together. Mobile UI testing frameworks are a plus.
- Good working knowledge of observability (RUM, APM, metrics, logs) and a track record of helping other engineers instrument their code well. Datadog experience is an advantage.
- Comfort working in a TypeScript codebase, and the curiosity to move across stacks you haven't owned before.
- Hands-on experience with a major cloud (GCP preferred) and infrastructure as code.
- A security mindset that shows up in your work by default: you think about threat surface, secrets and access when you design a pipeline or an environment, not after, and you're familiar with vulnerability management and secure-by-default practices.
- AI fluency. You use tools like Claude Code, Cursor or Copilot daily, you've built or improved workflows with them, and you have opinions about what makes an AI agent productive in a real codebase.
- A genuinely collaborative working style. You're energised by pairing, you go looking for feedback, and you'd rather sit next to an engineer than ticket them. You communicate clearly with people across engineering, QA, product and security.
- Strong ownership and judgement, with a bias toward simple solutions and finishing what you start.