Software Engineer (AI)

TL;DR

Software Engineer (AI): Building an endpoint AI observability platform that monitors and protects AI adoption on endpoints with an accent on data collection agents, inference pipelines, and customer interfaces. Focus on designing distributed systems, optimizing high-throughput data processing, and defining AI-native engineering practices using agentic coding tools.

Location: Fully remote across the US & Canada

Salary: $200K – $360K • Offers Equity

Company

Origin by Prelude builds the endpoint AI observability platform for organizations adopting AI, backed by Sequoia Capital, Brightmind Ventures, IA Ventures, and other top firms.

What you will do

• Own design and implementation from idea to release across the full stack: data collection agents, backend services, infrastructure, and frontend interfaces.
• Ship features with velocity and impact, obsessing over customer problems.
• Build and distribute internal agents to automate engineering workflows.
• Define AI-native engineering practices, including context, permissions, and tooling for agents.
• Design and operate distributed systems using AWS, EKS, Clickhouse, and Kafka against production SLAs.
• Drive decisions on storage schemas, API contracts, and scalable patterns in a multi-tenant environment.
• Collaborate with research and systems engineers to productionize their work.

Requirements

• Location: Must be in US or Canada for fully remote work
• AI-native engineering: fluent in Claude Code, Codex, OpenCode, with ability to redirect agents.
• Track record building data-intensive systems at scale (millions of operations, high-throughput processing).
• Deep knowledge of distributed systems: streaming, batching, backpressure, recovery, consistency.
• Performance engineering: complexity analysis, profiling, optimization under constraints.
• Modern systems programming (Rust preferred), strong Python fluency.
• Production experience with AWS/Kubernetes/EKS, event streaming (Kafka), React frontend.
• High agency and track record of identifying and completing important work.

Nice to have

• Background in observability infrastructure (Palantir, Datadog, etc.).
• High-throughput systems experience (HFT, real-time telemetry).
• AI infrastructure or applied ML (inference pipelines, embeddings, agents).
• Early-stage startup or founding-engineer experience.
• Open-source contributions or research in AI tooling.
• Data engineering with columnar/OLAP databases.
• OS internals (eBPF, Windows ETW, Apple ESF).
• Cross-platform expertise (Windows, macOS).

Culture & Benefits

• Fully remote team across US & Canada, built on trust, autonomy, and excellence.
• Generous healthcare, flexible PTO, home-office support.
• Empowerment to take ownership, move with purpose, and continuously improve.
• High standards for top performers aligned with the mission.
• Emphasis on quality, collaboration, and precision in fast-paced environment.
• AI tools to improve work streams.