Software Engineer, Distributed Systems & Security (all genders)

Build the secure link that lets AI agents work across private and public infrastructure while confidential data stays with its owner.

About Serinyx

Serinyx builds AI for high-stakes decisions on confidential data. On our decision-intelligence platform, AI agents break a hard question down, research it with checked citations and debate the findings under human review. The result is a verified, cited and signed report.

Our second product gives universities and research institutes an always-current, AI-built view of their research. We were founded in Saarbrücken in 2026 and are now building our engineering team.

The role

You start on our decision-intelligence platform, building the private edition that runs on a customer’s own servers. After three to five months, once its design is ready, you move to our hardest research problem: a secure link between that private deployment and our public cloud platform. AI agents on both sides should reason together across it without confidential data leaving the customer’s side. A research scientist in the team designs the link and its guarantees; you build it, test it and run it.

Why this role

• Two hard problems in one role: shipping software into customer data centres, then building a research-grade secure protocol.
• You build from a researcher’s design, with the researcher working next to you.
• Security you can check: every crossing is recorded, verified and open to an outside auditor.

What you will do in your first year

• First three to five months: build the private edition of the platform for customers’ own servers, with packaging, isolation between tenants and security hardening.
• Then, once the design is ready: build the link as a typed protocol in which only permitted kinds of message cross between the private and public sides, checked on both ends.
• Integrate the policy checks on the private side that decide what may cross, within a set leakage budget.
• Record every crossing in a tamper-evident log, and build the tool an outside auditor uses to verify it.
• Build the test harness: automated debates across the link at scale, leakage measurements, tamper tests and attacks, all reproducible. Then run a reference deployment end to end.

What you bring

• A degree in computer science or a related field.
• Several years designing and owning production distributed systems in Python, Go or Rust. Show us one.
• Security engineering: authenticated messaging, strict schemas, policy enforcement, isolation between customers.
• Shipping software into customer environments: containers, Kubernetes and Helm, on-premises or offline installs.
• Test harnesses that run thousands of automated jobs and produce reproducible measurements.
• Comfort moving between product work and work from a researcher’s specification.
• You turn a vague goal into a precise work order an AI coding agent can build from, and you can show us a time you caught an agent’s code or tests being wrong.

Nice to have

LLM serving (vLLM, SGLang) and constrained decoding; cryptographic engineering (hash chains, signatures, zero-knowledge proofs); policy engines (OPA); transparency logs (Sigstore, SCITT); red-team experience.

How we work

• One team, one backlog. Everyone builds from day one and works directly with our CTO, Dr Raja Naeem Akram.
• Owners, not ticket-takers. Each engineer owns parts of the codebase and leads the AI coding agents working in them: writing their work orders, reviewing every pull request and deciding what merges.
• A typical week. Much of your time goes into specifying and reviewing work done by AI coding agents; the hardest parts you write yourself.
• AI agents take the routine platform work. Infrastructure, deployment and monitoring are done by AI agents under engineering review, so your time goes into design and the hard problems. You still own what you build once it is live.
• Quality is part of the job. You write the tests for your own work and keep CI green. Done means tests pass, security scans are clean, docs are updated and container images are signed.
• Two-week cycles. Planning on day one, a demo on day ten and a short written retro.
• English first. English is our working language; German is welcome but not required.

What we offer

• Real ownership. An early role in a small team: you shape the product, the code and how we work, not a ticket queue.
• A modern stack. Python, FastAPI, Temporal, Kubernetes, React with TypeScript, and the best AI models for each task.
• Saarbrücken, hybrid. We are based in one of Europe’s leading centres for computer science, and we work hybrid.
• 30 days of holidays per year.
• International applicants welcome. If you come from outside the EU, we support you through the work-permit process, usually the EU Blue Card.

How to apply

Send your CV and one link that shows your work (code, a paper or a project you built) to [email protected] with the job title in the subject line. English or German is fine. The process has three steps: a call with our CTO, a technical interview on a problem typical of the role, with your usual AI tools, and a conversation with the founders.

Equal opportunity

We welcome applications from everyone, whatever their ethnic origin, gender, religion or belief, disability, age or sexual identity. You don’t need to include a photo or your date of birth.

Job Type: Full-time

Pay: 59.300,00€ - 64.600,00€ per year

Work Location: Hybrid remote in 66111 Saarbrücken