Dynamo AI
Product Manager, AI Governance & Compliance

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The Role
Every AI application needs policies that define acceptable behavior, and guardrails built and tuned against those policies. Legal, risk and compliance teams hold much of the knowledge those policies depend on. They have no prior experience or mandate to write policy definitions for guardrails or to annotate data, and there is usually no process that brings them into guardrail creation and optimization. They are also rarely the teams that buy our products, which are usually purchased by security and AI platform leaders.
As Product Manager for AI Governance & Compliance, you will design how these teams take part in policy writing, guardrail creation and guardrail optimization where no such process exists today. That means working out who needs to contribute, what they sign off on, and how their participation is secured through the economic buyer. It also means building the product workflows that make their contribution practical within the time they can give. This requires an understanding of how large enterprises assign responsibility and how teams outside the buying organization are brought into new work.
You will also support work on audit-ready evidence records and on turning regional regulations into enforceable guardrails. Over time, your scope will expand to AI system inventory and risk tiering, and to the procurement, privacy and legal reviews enterprises run on AI vendors. You will present to customers' senior risk and legal stakeholders, build credibility as an authority on these problems, and lead customer engagements when needed.
What You'll Work On
- A model for how legal, risk and compliance teams participate in policy writing, data annotation and guardrail review, including who contributes, at which step, and what they approve.
- Product workflows that fit that participation into how these teams already review and document decisions, with the least time asked of them.
- Evidence records that let customers reproduce and defend approval decisions under examination.
- Translating regulations that govern specific AI behavior, such as provisions of the EU AI Act and the UK Equality Act, into policies and guardrails.
- Later: AI system inventory and risk tiering, and reducing the time customers' procurement, privacy and legal teams need to approve Dynamo.
Reasons to use Rodeo
I’m in my final year doing Economics and I don’t know whether to apply for grad schemes now or do a masters first. What do you think?
Honest answer — it depends on where you want to end up. A lot of top grad schemes (Big 4, civil service, banking) don’t need a masters. Let’s look at the ones you’d be competitive for now, and we can decide if a masters actually adds anything.
Also worth knowing: most autumn 2026 applications are open now. Timing matters more than you think.
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Graduate Consultant — 2026 Scheme
Why you're a good match
StrongYour economics background and your summer at a regional bank line up with what PwC looks for on the consulting scheme. Applications close in four weeks.
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Why you're a good match
You’ve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon — deadlines close within the month.
Experience fit
Your summer at the bank plus your econometrics coursework map directly to the day-one responsibilities on this scheme — client modelling, market briefings, and deal support.
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Responsibilities
- Own the roadmap for legal, risk and compliance workflows against defined customer problems and success metrics.
- Map each customer's stakeholders: the economic buyer, the legal, risk and compliance teams whose input is needed, and the approvers. Secure those teams' participation through the buyer.
- Design and run engagement models with customers, such as responsibility assignments and review cadences, and turn what works into product.
- Lead engagements with model risk, compliance, legal and privacy teams, and present to senior risk and legal stakeholders.
- Translate regulatory requirements and customers' internal policies into product requirements, working with engineering and research.
- Work with the DynamoEval and DynamoGuard PMs on shared policies, evaluation evidence and reporting.
- Track AI regulation and supervisory guidance, and assess what each change means for customers and the roadmap.
Requirements
- 2 to 4 years of product management experience in GRC, regtech, legal tech, risk management or enterprise workflow software.
- Experience working directly with legal, risk, compliance or audit teams at large enterprises, and an understanding of their mandates, incentives and how they make and document decisions.
- A track record of bringing a team into a new process or responsibility it did not previously own, in an organization where that team did not report to you or to the project sponsor.
- Understanding of enterprise decision-making: how budget holders, reviewers and approvers differ, and how to secure time and sign-off from teams outside the buying organization.
- Working knowledge of how regulated enterprises govern models and AI, including model risk management practices such as SR 11-7 and frameworks such as the EU AI Act, NIST AI RMF and ISO/IEC 42001.
- Enough technical understanding of LLMs, evaluations and guardrails to discuss precision, recall and false positive tradeoffs with engineers and explain them to non-technical reviewers.
- Strong writing and presentation skills, with experience producing documents that hold up to review by legal and risk teams.
- Willingness to spend 4 to 6 weeks per year at customer sites, and more during large contract engagements.


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Nice to Have
- Prior experience in model risk validation, compliance, internal audit or risk consulting.
- Experience with privacy (GDPR, DPIAs) or third-party risk management.
- Experience designing annotation, labeling or review workflows for subject matter experts.
- Legal training or experience interpreting regulation.
- Experience in financial services or insurance.
Why Join Us
- Define how legal, risk and compliance teams take part in governing AI at the enterprises adopting it.
- Work directly with risk, legal and compliance leaders at Fortune 500 enterprises.
- Own a product area end to end at a founder-led startup.
- Competitive compensation, equity and benefits.
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