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Pavo AI

Founding Systems Engineer (Infrastructure)

London
Posted 1 day ago
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About Pavo

Pavo is building Enterprise Superintelligence: compounding systems that take ownership of business outcomes and work with humans to deliver them.

We believe that while foundation models are necessary, they are not sufficient. The hard problem is systems intelligence: end-to-end architectures that understand a company's code, data, and decisions, and improve themselves through experience.

We are assembling a small, senior team of researchers and engineers obsessed with systems-first intelligence. Our current team consists of PhDs and ML engineers from top applied ML and coding agent companies, with a heritage of shipping systems at Spotify, ShareChat, and Sourcegraph scale.

Our team has built impressive momentum with a small group of highly capable engineers and researchers.

The Opportunity

As a Founding Systems Engineer, you will lead our ML Infrastructure team, driving DevOps, MLOps, and Agent Ops across both R&D and production environments. You will own the automation of release and evaluation processes and collaborate closely with cross-functional teams to support their projects.

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.

Start with a chat, not a search bar

Grad scheme, placement, apprenticeship? Not sure what you want yet — that's fine. Your agent talks it through with you and turns "I have no idea" into a shortlist.

P

Graduate Consultant — 2026 Scheme

PwC·London, UK
£35,000/yr

Why you're a good match

Strong

Your 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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It searches the market for you

Every day your agent scans the market matching roles against what actually matters to you, not just keywords on a CV.

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.

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Strong

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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Strong

Only hits

No noise. No "maybe this fits." Just roles with a clear explanation of why they're right — and where to focus when applying.

This is a critical role for a builder who thrives at the intersection of ML research infrastructure and production systems, and wants to define the engineering culture of a fast-paced AI company from the ground up.

What You'll Build

  • ML Infrastructure Leadership: Lead the ML Infrastructure team working on DevOps, MLOps, and Agent Ops for both R&D and production environments.
  • Release & Evaluation Automation: Automate the release and evaluation processes for research and production, ensuring reliable and efficient delivery of ML systems.
  • Cross-Functional Collaboration: Collaborate with cross-functional teams and support their projects, acting as a key enabler across the organisation.

What We Are Looking For

  • MLOps & DevOps Tooling: Proven track record of working with systems such as ArgoCD, Kargo, Jenkins, Vertex AI, SageMaker, and similar platforms.
  • ML Infrastructure Experience: Proven track record of working on ML research and production infrastructure.
  • Infrastructure as Code: Knowledge of IaC tools such as Terraform and Helm.
  • Cloud Expertise: Excellent familiarity with at least one of the hyperscaler clouds (GCP, AWS, Azure), and familiarity with the others.
  • Engineering Excellence: Excellent software engineering and problem-solving skills.
  • Communication: Excellent interpersonal and communication skills.

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Why Join Us

  • Founding Equity: Significant ownership in a company tackling the next layer of the AI stack.
  • Technical Challenge: Solve novel infrastructure problems related to secure agentic execution and "orgs in a box."
  • World-Class Team: Collaborate with a dense talent cluster of researchers and engineers who have shipped products serving hundreds of millions of users.

Pavo is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.

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Skills

MLOps
DevOps
Agent Ops
Infrastructure as Code
Cloud Computing
Software Engineering
Problem Solving
Communication
ArgoCD
Kargo
Jenkins
Vertex AI
SageMaker
Terraform
Helm

Location

London, England, United Kingdom

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