Founding Systems Engineer (Infrastructure)
Build the foundational infrastructure powering massive agentic runs
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 contribute to the development of the foundational infrastructure that powers massive agentic runs tackling complex data workloads live. You will be part of team that architects the secure execution environments and compute substrate that allow thousands of autonomous AI engineers to write code, run experiments, and deploy software safely within our customers' environments.
This is a critical role for a builder who loves deep infrastructure challenges, from low-level container isolation to high-level GPU orchestration; and wants to define the engineering culture of a new kind of fast paced enterprise infrastructure.
What You'll Build
You will own the infrastructure strategy and implementation, focusing on:
- →Core Database Engine: You'll contribute to the core database engine, driving improvements across ingestion, query execution, indexing, and storage to support massive-scale knowledge systems.
- →High-Performance Distributed Systems: Design, build, and operate high-performance distributed systems. You will identify and resolve performance bottlenecks to scale infrastructure to the next order of magnitude.
- →Sandboxing & Secure Execution: Design and deliver the isolated execution environments (using container runtimes, gVisor, or Firecracker) that allow our agents to safely execute untrusted code, manage secrets, and enforce strict policies (OPA) without risking the host environment.
- →Orchestration & Compute Strategy: Architect the primitives for task scheduling, fault tolerance, and large-scale compute management. You will collaborate on defining abstractions for GPU resource management and efficient scheduling for heavy ML workloads.
- →Technical Leadership: Define long-term technical direction and guide system evolution, translating ambiguous requirements into concrete engineering roadmaps.
What We Are Looking For
We are seeking a seasoned engineer who has seen infrastructure break at scale and knows how to design for resilience.
Core Qualifications
- →Systems Depth: 8+ years of engineering experience with a track record of owning complex, critical systems.
- →Production Operations: Have experience operating production clusters at scale (e.g., Kubernetes or other orchestration systems).
- →Cloud & IaC Fluency: Fluency in cloud environments (AWS, GCP, Azure) and IaC tools (Terraform or similar).
- →Linux & Observability: Experience with Linux systems, CI/CD pipelines, and modern observability stacks (Prometheus, Grafana, etc.).
- →Secure Execution: Practical knowledge of sandboxing patterns, secure execution, and policy enforcement (OPA). You understand the security implications of running arbitrary code at scale.
Nice to Have
- →Experience with GPU scheduling and optimizing ML inference workloads.
- →Background in building or supporting simulation environments or synthetic data pipelines.
- →Deep experience in client infrastructure: build systems, performance, distribution, or observability.
- →Early-stage startup experience shipping zero-to-one infrastructure.
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.