
Tracer provides real-time visibility into HPC pipelines for scientific computing. It uses eBPF-powered OS-level data extraction to capture low-level signals across nodes. The SaaS platform integrates…

Tracer provides real-time visibility into HPC pipelines for scientific computing. It uses eBPF-powered OS-level data extraction to capture low-level signals across nodes. The SaaS platform integrates…
Product: eBPF-based observability and automated root-cause investigation for high-compute data and scientific pipelines
Target users: Bioinformatics, pharma/biotech, HPC, AI/ML teams running large-scale pipelines
Founded: 2023
Stage / funding signal: Has raised institutional capital including an $18.1M Series A; total reported ~$30M
Observability and incident investigation for HPC, bioinformatics, and large-scale computational pipelines
2023
Biotechnology
$18.1M
Announced Series A of $18.1M (reporting indicates ~$30M raised in total to date).
“Company site lists board and investor-affiliated individuals including Andreas Goeldi (b2venture) and several angel investors”
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About the job
If your answers are yes, then you should keep reading.
🚀 About The Role
Tracer is building agentic alert investigation for production data pipelines.
Teams already have alerts. Tracer investigates pipeline incidents before they page your team, filtering noise, correlating evidence across your stack, and producing an evidence-based RCA for the issues that actually matter.
We’re hiring a Founding Lead Engineer in London to own core architecture and ship an agent that produces grounded RCAs (and fix suggestions) for a set of high-value alerts. Humans stay in control of production decisions.
💻 You’ll love our tech stack
💼 Key Responsibilities
You’ll own the core systems that turn an alert into a defensible investigation and RCA. In practice, you will:
🌟 What We Are Looking For
💸 Compensation
We will be transparent and competitive.
⚒️ Our Recruitment Process
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Architect and build the core alert, investigation, root cause analysis (RCA) pipeline in Python
Design and implement key systems including:
Alert ingestion + normalization
Context enrichment + correlation
Problem framing outputs
Hypothesis orchestration engine
Investigation execution runtime
Investigation artifacts + reporting
Drive core architecture decisions and ensure the system is observable, auditable, and reliable from day one
Partner with founders to ship a small set of high-value alert types that work extremely well, then expand coverage deliberately
Build customer-ready integrations across the pipeline stack
Educate and guide future engineers, setting a high bar for technical quality, speed, and pragmatism