Software Engineer

Origin is building an AI observability platform for organizations adopting AI. They are seeking a Software Engineer to design and implement solutions across their tech stack, focusing on data collection, analysis, and customer interface.

Responsibilities:

• Obsess over customer problems and ship for velocity and impact over technical pedantry
• Ship across the stack - agent, backend, infrastructure, and frontend - wherever the work is that week
• Build internal agents that automate the repeatable parts of engineering and distribute them across the team
• Define how AI-native engineering works at Origin: the context, permissions, and tooling our agents need to do real work
• Design and operate distributed systems using AWS, EKS, Clickhouse, and Kafka against real production SLAs
• Drive technical decisions on storage schemas, API contracts, and the patterns that hold up at scale in a multi-tenant environment
• Work alongside research and systems-internals engineers to turn their work into reliable production software

Requirements:

• AI-native engineering practice: prolific use of Claude Code, Codex, and OpenCode, with the judgment to know when an agent will go off the rails and the skill to redirect it
• Track record of building data-intensive systems at scale (millions of concurrent operations, high-throughput event processing, distributed coordination)
• Deep understanding of distributed systems principles: streaming, batching, backpressure, recovery, and consistency models
• Performance engineering mindset: complexity analysis, profiling-driven optimization, and discipline under resource constraints
• Modern systems programming experience, Rust preferred (we value problem-solving ability over specific language expertise)
• Strong working fluency in Python across services, inference pipelines, and tooling
• Production experience with cloud infrastructure (AWS preferred), Kubernetes (EKS or equivalent), and event streaming (Kafka or equivalent)
• Comfortable working in our React frontend to deliver functionality to end users
• High agency, with a track record of identifying important work and finishing it
• Obsess over customer problems and ship for velocity and impact over technical pedantry
• Ship across the stack - agent, backend, infrastructure, and frontend - wherever the work is that week
• Build internal agents that automate the repeatable parts of engineering and distribute them across the team
• Define how AI-native engineering works at Origin: the context, permissions, and tooling our agents need to do real work
• Design and operate distributed systems using AWS, EKS, Clickhouse, and Kafka against real production SLAs
• Drive technical decisions on storage schemas, API contracts, and the patterns that hold up at scale in a multi-tenant environment
• Work alongside research and systems-internals engineers to turn their work into reliable production software
• Background in real-time monitoring or observability infrastructure (Palantir, Datadog, Honeycomb, Chronosphere, the data side of Stripe or Cloudflare)
• Background in high-throughput systems (high-frequency trading, real-time telemetry, low-latency distributed systems)
• Background in AI infrastructure or applied ML, particularly inference pipelines, embedding and topic systems, or agent orchestration
• Prior founding-engineer or early-stage startup experience
• Open-source contributions or published research in AI tooling, agent frameworks, or developer infrastructure
• Data engineering experience with columnar databases or OLAP / time-series systems
• Deep OS internals knowledge (Windows ETW, Apple ESF, eBPF)
• Cross-platform systems expertise (Windows and macOS)