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Cloud • Computer Vision • Information Technology • Sales • Security • Cybersecurity
The role involves developing high-volume distributed systems in Golang, collaborating on cloud protocols, and ensuring system scalability and reliability.
Top Skills:
AWSAzureCassandraElasticsearchGCPGoKafka
3D Printing • Aerospace • Hardware • Software • Manufacturing
The Senior Software Engineer, Backend will design and maintain scalable backend services for artificial-gravity space stations, collaborating with cross-functional teams to ensure secure and reliable systems.
Top Skills:
C++DockerGoKubernetesLinuxPythonRust
Artificial Intelligence • Computer Vision • Machine Learning • Software
As a Senior Staff Software Engineer and Tech Lead Manager, you'll design and implement key server systems, provide mentorship, and collaborate with leadership on strategic initiatives for geospatial AI.
Top Skills:
3D ReconstructionComputer VisionGeospatial AiNetworkingServer SystemsXr
Why This Role
The AI era is breaking every assumption about data protection. Sensitive data moves faster, through more systems, with higher stakes than ever before. Traditional privacy and governance tools can't keep up — they put up a cookie banner and call it compliant. We go deeper: real-time enforcement of consumer privacy choices across every device, system, and third-party application where data lives.
This is backend engineering where correctness matters, latency matters, and scale is real. You'll build the infrastructure that replaces the legacy tools failing enterprises today — and you'll see your work running live on sites used by millions of people.
What You'll Work On
You'll build reliable, high-performance systems that make sense of messy, high-stakes data flowing through databases, pipelines, SaaS tools, websites, and mobile apps.
Specifically:
- Design and build Go microservices that process distributed data flows and support real-time governance decisions across an organization's entire stack
- Develop clean, well-versioned APIs that orchestrate permissions, data directives, and automated actions across external systems
- Build distributed pipelines and event-driven architectures that transform structured and unstructured data and feed downstream intelligence
- Own the full lifecycle — from understanding the customer problem through design, implementation, deployment, monitoring, and iteration
- Apply resilience patterns (timeouts, retries, circuit breakers) to keep systems predictable under real-world load
- Drive performance through concurrency tuning and efficient resource usage
- Contribute to architecture decisions: service boundaries, data models, queue/stream strategy, and AI integration points
- Talk directly to customers to understand their pain points and translate requirements into scalable system designs
What Makes This Different
- You'll own real problems, not tickets. Engineers here take a customer problem and figure out how to solve it — you're not waiting for a product manager to hand you a spec. You think through the problem, define the approach, and build it.
- You'll never be bored. You won't be on the same product for three years. You'll move across problems — maybe six months on one, then a new challenge, a new product, a new domain. There's always something new to learn and build.
- Your code runs on real sites, for real users. This isn't internal tooling. You'll see your work live on major consumer-facing websites and apps, processing millions of decisions daily.
- AI assistants are part of the workflow. We use Cursor, Claude Code, Copilot, and similar tools daily. We expect engineers to leverage them — and we evaluate candidates using them during interviews.
- The company is at an inflection point. We're well-positioned to take over this market. The equity upside is real, the customer list is growing fast, and the engineering team has a direct line to the company's success.
What We're Looking For
We're hiring at both mid-level and senior levels — what matters most is that you can think through complex problems independently and ship production systems that work at scale.
- Strong backend engineering foundation in Go or similar systems languages
- Experience building APIs, distributed systems, or microservices in cloud-native environments (AWS/GCP/Azure)
- Familiarity with databases and storage systems: Postgres, DynamoDB, ScyllaDB, Redis, Elasticsearch, or similar
- Understanding of distributed-systems fundamentals: concurrency, queues/streams, transactions, event-driven patterns
- Experience with gRPC, REST, and service-to-service communication
- Comfort with Kubernetes, containers, and operational concerns (security, networking, resource management)
- Interest in modern AI/data tools (LLM APIs, embeddings, retrieval)
- Experience using AI coding assistants (Cursor, Claude Code, Copilot, or similar) in your daily workflow
- Curiosity, grit, and a drive to figure things out without heavy direction — startup experience is a plus
- CS degree or equivalent practical experience building production systems
What separates great candidates from good ones: Can you take a complex, ambiguous problem, break it down, ask the right questions, and figure out what needs to be built? That's the skill we're hiring for.
Language and framework experience matters less than your ability to think.
The Team
The engineering team is ~15 people, entirely co-located at our San Francisco headquarters. This in-person collaboration drives fast iteration, direct customer interaction, and the kind of hallway conversations that make startups move. You'd report to VP of Product & Engineering.
This is a hybrid role — in-office 3 days a week at our SF HQ (SoMa)
Compensation
$160,000 – $220,000 base salary + equity + benefits
The range reflects both mid-level and senior experience. Compensation decisions factor in skills, experience, and market conditions. Benefits include full medical/dental/vision, 401(k), and equity. Three company-wide events per year in San Francisco.
Ketch San Francisco, California, USA Office
23 Geary St, San Francisco, CA, United States, 94108
What you need to know about the San Francisco Tech Scene
San Francisco and the surrounding Bay Area attracts more startup funding than any other region in the world. Home to Stanford University and UC Berkeley, leading VC firms and several of the world’s most valuable companies, the Bay Area is the place to go for anyone looking to make it big in the tech industry. That said, San Francisco has a lot to offer beyond technology thanks to a thriving art and music scene, excellent food and a short drive to several of the country’s most beautiful recreational areas.
Key Facts About San Francisco Tech
- Number of Tech Workers: 365,500; 13.9% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Google, Apple, Salesforce, Meta
- Key Industries: Artificial intelligence, cloud computing, fintech, consumer technology, software
- Funding Landscape: $50.5 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Sequoia Capital, Andreessen Horowitz, Bessemer Venture Partners, Greylock Partners, Khosla Ventures, Kleiner Perkins
- Research Centers and Universities: Stanford University; University of California, Berkeley; University of San Francisco; Santa Clara University; Ames Research Center; Center for AI Safety; California Institute for Regenerative Medicine
