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Staff Engineer

πŸ•’ 3 days ago
GoPythonDistributed SystemsAI Agents
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πŸ“œ Description

  • Build investigation tools and security data integrations, improving agent context, evidence recall, cost, and latency.
  • Develop evaluations to measure the accuracy and sourcing of agent findings and guide model, prompt, and tool changes.
  • Evolve service boundaries and failure handling as platform capabilities grow.
  • Improve API governance, testing, and observability practices.
  • Partner with product management to translate case needs into technical specifications.

πŸ› οΈ Requirements

  • Track Record: You've designed and shipped distributed systems that are still running in production years later, and you can tell us what you'd change. Typically this comes from time in a Staff, Principal, or Lead role.
  • AI/LLM Engineering: You've taken AI agents from prototype to production across multiple model providers, and built tool-calling agent loops, evaluation harnesses that catch regressions before release, and guardrails against hallucination.
  • AI-Native Development: You build with coding agents every day and know how to review and verify what they produce.
  • Language Expertise: Deep expertise in Go or Python and strong in the other, including the runtime, concurrency models, and memory management of each.
  • Data Architecture: You've worked across a relational system of record, columnar analytical stores that query large datasets, and vector search. You know when each fits, and you've run zero-downtime schema migrations.
  • API Design: You've designed schema-first, contract-driven APIs with generated clients and built-in validation, including streaming APIs for live updates.
  • Durable Systems: You've built long-running workflows on durable execution and event streaming, and you treat idempotency, retries, and recovery from partial failure as design requirements.
  • Data Pipelines: Experience building event-driven ingestion pipelines that move large volumes of structured data from object storage into analytical systems.
  • Cloud Architecture: Experience with a major cloud provider, infrastructure as code, and container orchestration, including designs that keep each customer's or case's data isolated.
  • Security Domain: Experience building security products, or familiarity with digital forensics, incident response, or security telemetry.
Full job description

Who We Are

MOXFIVE helps enterprises respond to, recover from, and build resilience against cyber attacks. Our responders have led many of the most prominent security investigations in the world, from ransomware that takes a business offline to nation-state intrusions. When an attack hits, we work alongside the executives, outside counsel, and insurers who need answers fast and need answers they can defend.

Intelligent Insurer named MOXFIVE Cyber Security Consulting Team of the Year in 2024 and 2025, and Inc. has named us one of its Best Workplaces three times.

We are building an AI investigation platform that puts that frontline experience behind every analyst on a case.

Who You Are

You are a technical leader who looks past the code to the system around it. You make high-stakes decisions under ambiguity and balance speed of delivery with long-term maintainability. You raise the team's quality through design reviews, code reviews, and the patterns you introduce.

You work well among strong peers and know when to lead and when to defer to someone closer to the problem. You pick the right problems to solve and can explain your architectural choices to engineers and executives alike.

The Impact You'll Have

You'll extend what our agents can do, measure whether their findings hold up, and keep the services around them solid as the platform grows. This is a hands-on role, and most of your time goes to designing and building.

Your core responsibilities will include:

  • Agent Capabilities: Adding investigation tools and integrations with security data sources, and improving how agents manage context, recall evidence, and trade off cost against latency.

  • Investigation Quality: Building the evaluations that show whether agents reach correct, well-sourced findings, and using them to decide model, prompt, and tool changes.

  • Platform Architecture: Evolving service boundaries and failure handling as new capabilities land.

  • Engineering Standards: Raising our practices for API governance, testing, and observability.

  • Cross-Functional Leadership: Working with product management to turn case needs into technical specifications.

What You'll Bring

  • Track Record: You've designed and shipped distributed systems that are still running in production years later, and you can tell us what you'd change. Typically this comes from time in a Staff, Principal, or Lead role.

  • AI/LLM Engineering: You've taken AI agents from prototype to production across multiple model providers, and built tool-calling agent loops, evaluation harnesses that catch regressions before release, and guardrails against hallucination.

  • AI-Native Development: You build with coding agents every day and know how to review and verify what they produce.

  • Language Expertise: Deep expertise in Go or Python and strong in the other, including the runtime, concurrency models, and memory management of each.

  • Data Architecture: You've worked across a relational system of record, columnar analytical stores that query large datasets, and vector search. You know when each fits, and you've run zero-downtime schema migrations.

  • API Design: You've designed schema-first, contract-driven APIs with generated clients and built-in validation, including streaming APIs for live updates.

  • Durable Systems: You've built long-running workflows on durable execution and event streaming, and you treat idempotency, retries, and recovery from partial failure as design requirements.

  • Data Pipelines: Experience building event-driven ingestion pipelines that move large volumes of structured data from object storage into analytical systems.

Nice to Have

  • Cloud Architecture: Experience with a major cloud provider, infrastructure as code, and container orchestration, including designs that keep each customer's or case's data isolated.

  • Security Domain: Experience building security products, or familiarity with digital forensics, incident response, or security telemetry.

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