Principal Software Engineer

About Sondera

AI agents act on instructions written in natural language, and much of what people mean goes unsaid. A sequence of steps that are each allowed can still do damage. Sondera works on the open problem of semantic integrity: every action an agent takes carries out what an authorized person meant. Enterprise security teams write rules in plain language, and we autoformalize them into policy. Before each action runs, our policy engine renders a verdict given the agent's trajectory: everything the agent has done in the session. The same action, in the same state, under the same policy, gets the same verdict. We publish our research at ICML and NeurIPS workshops and present it at Black Hat Arsenal, BSides and [un]prompted. Our open-source hooks and policy engine already govern coding agents, and enterprise customers run our platform. Our team has built products at Cylance, Databricks, HiddenLayer, NetRise and Obsidian Security, and we're backed by Decibel, Runtime Ventures and Aviso Ventures.

About the role

You own the record of everything AI agents do while Sondera governs them, and the services that write it. Security engineers rely on that record to see what their agents did and to prove it to auditors. You decide how agent events are modeled across every runtime, how they're stored so writes stay fast and reads stay cheap, and how a schema change reaches production safely. You'll turn our AI security research into enforceable, systems-level controls.

Principal is a senior individual-contributor role; you lead through design and review.

In your first year you will

• Keep trajectory reads fast at enterprise scale, with views built as the events are written.
• Hold verdict latency steady when many actions arrive on one trajectory at once.
• Ship schema changes that never take production down, including for customers who run Sondera themselves.
• Design a versioned event model that represents every agent runtime, including agents that delegate to other agents.
• Make every verdict and finding cite the exact events behind it, in a record customers can check and export.

You may be a good fit if you

• Have designed and run a write-heavy data system in production, owning its schema as well as its service.
• Know a relational database deeply, ideally Postgres: query plans, indexes, locking, write-ahead logs and migrations.
• Write production code in whatever systems language you know best.
• Design event schemas and contracts that evolve without breaking their readers.
• Use coding agents daily, and review what they write as closely as a colleague's work. A person who owns the code approves every change to production.

Prior security experience is useful but not required. Caring that the record of what an agent did is complete and correct matters more.

Strong candidates may also have

• Production Rust experience.
• Event sourcing, change-data capture or read projections at scale.
• Trace and event formats such as OpenTelemetry or OCSF.
• Work on representing agent trajectories, multi-agent systems or data provenance.
• Software that enterprises run themselves, with upgrade paths across versions.
• A public record of your work: papers, talks, open source or technical writing.

Our stack

Rust for the services that render verdicts, Python for AI, and TypeScript for the web applications. Agent events are stored in Postgres. Policy compiles to a formal policy language. The platform runs in Google Cloud and in customers' own infrastructure.

How we work

We study four open problems: turning written rules into policy, enforcing that policy at runtime, making agent behavior inspectable, and overseeing fleets of agents, including agents that delegate to other agents, without a person reviewing every action. The people who write our papers also ship the product, so our research meets agents doing real work, and what breaks sets our next question. Whoever builds something helps run it. We build Sondera with coding agents and govern them with it. We settle technical disagreements with evidence. We work remotely: we start from written intent, review each other's changes async, write decisions down where everyone can read them, and flag any decision we can't undo before we make it.

Logistics

• Location: Remote, United States. We meet in person three times a year.
• Compensation: Base salary of $240,000–$280,000 USD, plus equity.
• Benefits: Medical, dental and vision coverage for you and your dependents; a 401(k) plan; unlimited paid time off, and we expect you to take about a week each quarter, plus paid holidays.
• Visa sponsorship: We sponsor visas, including transfers, though not for every role or candidate.
• Interview process: screen → work-sample interview and review → systems interview → career deep dive (a structured walk through your past roles) → references. We aim to make a decision within two weeks of your screen.
• Using AI in your application and interviews: Use AI to prepare, and to polish an application you wrote yourself. In the work sample you'll build without AI, then extend your work with a coding agent, so we see both how you design on your own and how you check an agent's output. The other interviews are without AI.

We encourage you to apply even if you don't meet every qualification.