Lead DevOps Engineer

Elliptic has helped trace and disrupt over $21.8 billion in illicit crypto laundered across blockchains, from sanctioned nation states to organized crime networks hiding funds through token swaps and unregulated exchanges. It’s how compliance and investigations teams fight back, tracking and screening transactions with 99% market coverage.

The infrastructure behind all of this needs to be as resilient and sharp as the intelligence it delivers. We're looking for a Lead DevOps Engineer to own and evolve our DevOps practices. This is a role for someone who combines deep technical ability with a genuine passion for growing the team. You'll lead a team of DevOps engineers while staying close to the technical work, setting direction on infrastructure, automation, and reliability.

The impact you will have:

As a Lead DevOps Engineer at Elliptic, you will have a deep impact across the company by championing DevOps, security, and reliability principles. You’ll help build a culture of automation, efficiency, and continuous improvement, empowering teams to deliver secure, high-quality software with confidence. Current major projects include delivering AI Gateway and supporting LangChain/LangGraph infrastructure for Elliptic's AI products, managing disaster recovery (DR) infrastructure, and administering Kubernetes clusters across multi-region AWS environments. You’ll work alongside experienced and passionate engineers who enjoy solving tough challenges and learning from one another. This is a hands-on team Lead role where you will balance technical expertise with team leadership.

Elliptic is building an AI fluent workforce. Across our Product, Engineering, Design and Intelligence we’re going beyond giving everyone the tools. We’re setting new standards. Using AI to transform how we build and work every day to deliver on our market opportunity. Put another way our teams iterate alongside agentic systems applying judgement to build world class systems.

This role requires 'Transformative' AI fluency. This means you've already made production decisions about how AI systems get built, evaluated, and used responsibly, and you're ready to raise the bar for the engineers around you from day one.