Posting record
Open 12+ days
- Petual's site dates the posting
- Ghostless first sees this listing
- Last checked: still up
How we know
It hasn't been reposted, listed twice, or left up unusually long, and the posting doesn't say it's a talent pool.
Ghostless records the day it first sees a posting, so a repost can't reset its age. This one was already up when Ghostless started tracking Petual, so its true age is longer.
Last checked Nov 2, 2026.
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Upload your resumeWhat the posting discloses
Not stated: Pay, real vacancy, AI screening.
Why these three
Ontario requires postings from employers with 25 or more staff to state the pay, whether the vacancy exists, and whether AI screens applicants.
Some employers add pay only on their own site. Check the original posting before you rule it out.
Skills mentioned
About the role
Petual is the AI-powered control tester for the modern enterprise. Our agents test whether a company's financial, operational, and technology controls actually work, and trace every conclusion to its source.
The hard part isn't speed. It's being right. External auditors re-perform our work, so precision on sample 1 has to equal precision on sample 400, and an agent that can't support a conclusion has to say so rather than guess. We're backed by Andreessen Horowitz; the team comes from Stripe, Retool, and Lyft; and public companies already run their SOX programs on Petual.
The Opportunity
The interesting problem is not getting an agent to test a control once. It is knowing whether it was right across hundreds of controls, for customers whose methodologies all differ, where the ground truth is a senior auditor's judgment rather than a label in a dataset. Building the harness and the evaluation that make that tractable is the core of this role, and it would be yours to own.
What You'll Do
- Own the agent harness at the core of the product: the workflows, checkpoints, and evaluation that keep long-horizon agents reliable across hours of testing
- Design and own the backend services and APIs that carry evidence from ingestion, through analysis, to auditor-ready output
- Build integrations with the systems our customers keep evidence in: cloud infrastructure, identity providers, ticketing systems, ERPs, and more
- Design the data models and system architecture that have to hold up as our customer base and control volume grow
- Write code and design systems with security and data integrity in mind, given the sensitivity of the evidence our customers share with us
- Partner directly with our customers to craft and ship the features that matter most to the people actually doing the testing
What We’re Looking For
- Experience building on LLMs and agentic systems: harnesses, long-horizon agents, evals, or resilient workflows that survive contact with messy real-world input
- Experience building enterprise SaaS products that handle sensitive customer data
- Comfort working across the stack: solid backend fundamentals (APIs, data modeling, distributed systems) plus enough frontend fluency to ship a feature end to end
- Experience with AWS, Kubernetes, and infrastructure as code
- Experience in fintech, audit, governance, risk, compliance, or another regulated environment
- A track record of high ownership at an early- or growth-stage startup, where you shaped not just the code but the product and the process around it
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