SlipstreamJobs tracks this role from the company's public career site. Apply directly on the employer's site.
Salary: USD 200,000 - 265,000 / annual
Pallet is building AI agents to transform the physical economy, a $12 trillion global industry. The company has raised $50M from top investors including General Catalyst, Bessemer Venture Partners, and Bain Capital Ventures, achieving 700% revenue growth in under two years. Pallet's mission is to increase supply chain efficiency by automating manual workflows—from scheduling and appointment setting to data entry and load management—through its flagship platform and newest product, CoPallet, which features AI agents that understand and execute requests in real time.
As a Member of Technical Staff, Infrastructure Engineer, you will be one of the first infrastructure hires with significant scope and real ownership. You'll work directly with founding engineers who built and still own Pallet's infrastructure. This is a high-stakes role focused on solving the company's hardest scaling and reliability problems while setting technical direction for how Pallet operates at scale.
Key responsibilities include:
- Scaling the platform to millions of AI agent runs per day, solving capacity, performance, and reliability challenges
- Making the platform portable across clouds and on-premises customer environments
- Working through complex enterprise integration requirements including identity, private networking, certificate-based authentication, and data residency
- Owning observability and incident response, from alerting and on-call to post-mortems, ensuring issues don't recur
- Improving developer productivity by making local development, CI, deployments, and production debugging fast and dependable
The role emphasizes pragmatism, leaning toward proven technology, and trusting engineers to use their judgment. You'll have a direct line from your work to business impact.
REQUIREMENTS:
- 5+ years in infrastructure, platform, or SRE roles, ideally at a company or team you joined early and helped scale. Depth and judgment valued over exact years.
- Real depth in at least one area: databases, distributed systems, cloud infrastructure, observability, or application frameworks and runtimes. Production experience and hard-earned scars preferred over buzzwords.
- Track record of grounding decisions in evidence: setting SLOs, prioritizing performance work, planning capacity, finding bottlenecks, understanding where systems break.
- Nice to have: experience with TypeScript, Postgres, Redis, Google Cloud, OpenTelemetry, and Datadog.
