The vacancy is well-structured and informative, providing clarity on responsibilities, compensation, and company background.
Job description
## Who We Are
Galaxy is a global leader in digital assets and data center infrastructure, delivering solutions that accelerate progress in finance and artificial intelligence. We believe that blockchain and digital asset innovation will transform how value moves through the world – and we’re building the products and services to make that future a reality. Our institutional digital assets platform spans trading, investment banking, asset management, staking, self-custody, and tokenization technology. We also invest in and operate cutting-edge data center infrastructure to power AI and high-performance computing, addressing the growing demand for scalable energy and compute in the U.S. We work at the intersection of finance and technology, helping institutions, startups, and developers navigate a digitally native economy. Led by CEO and Founder Michael Novogratz, our team blends deep crypto expertise with institutional experience and a shared commitment to shaping the future of Web3 and AI. Galaxy is headquartered in New York City, with offices across North America, Europe, the Middle East, and Asia. To learn more about our businesses and products, visit www.galaxy.com.
Responsibilities
## What You’ll Do
- Lead the team - Develop the engineers on the team. Both tracks should build expertise that compounds — no dead-end paths.
- Set the bar for technical excellence, operational rigor, and customer-facing craft.
- Bring on new engineers as the team evolves — measured, deliberate hiring rather than scale-up.
- Own the platform - Hold the technical strategy for the shared platform: compute, networking, observability, CI/CD, validator clusters, the data plane, secrets and key management.
- Major direction is set with the Head of Engineering, Platform and Edge; you own the call within that.
- Make the build/buy/reuse calls. Decide what gets generalized into shared platform capability versus what stays bespoke to a single engagement.
- Own production reliability for institutional-grade systems running in production.
- Run the operational machinery - Operate the rotation model end-to-end: deploy engineers into client engagements, rotate them back to harden the platform, sequence the moves so both tracks feed each other rather than drift apart.
- Run team logistics — staffing across engagements, capacity planning, on-call rotation, cadence of planning and reviews, incident response process.
- Coordinate across DIS, client-facing teams, and engagement leads so the right engineers are on the right work at the right time, and commitments to clients are sequenced against platform reality.
- Keep the team's operating system simple. Cadences, rituals, and process should compound clarity, not overhead.
- Deliver on engagements - Once an engagement is greenlit, own the team's execution against it — staffing, sequencing, technical quality, and what gets shipped.
- Step into client conversations at technical inflection points when the engagement benefits from engineering leadership at the table.
- Make sure lessons from engagements feed back into platform direction, not just engagement-specific code.
Requirements
## What We’re Looking For
- A track record leading platform, infrastructure, or distributed-systems engineering teams in production-critical environments — financial infrastructure, custody, exchanges, payments, or comparable high-stakes domains.
- Experience leading small, senior teams. You know how to get leverage from a handful of strong engineers without adding headcount as the answer to every problem.
- Demonstrated operational chops — you've run the logistics of a team that ships across multiple concurrent workstreams. Staffing, sequencing, cadences, incident response. You can hold the whole picture in your head and keep it moving without bureaucracy.
- Strong technical depth. You don't have to write production code, but you should be able to read it, review architecture critically, and earn the respect of senior and staff engineers on technical merit.
- Experience operating in or alongside a forward-deployed, embedded, or solutions-engineering model.
- Comfort being customer-facing when the engagement calls for it. Tier-1 institutional clients expect engineering leadership at the table on technical decisions.
- High agency, low ego. We operate decentralized command — you'll own a clear mandate and be expected to drive within it without waiting for permission.
- Crisp judgment about when to generalize and when to stay bespoke. The platform thesis only works if you can tell the difference.
- Embrace and champion the thoughtful adoption of AI to improve team performance and business outcomes.
- Leverage AI tools (e.g., generative AI, automation platforms, data copilots) to improve productivity, decision-making, and output quality in your day-to-day work.
Conditions
## Bonus Points
- Blockchain / protocol experience — staking, validators, MPC, custody, DeFi protocol integration, tokenization infrastructure.
- Experience with MPC, HSMs, threshold signing, or secure enclaves.
- Background working with tier-1 financial institutions (banks, asset managers, custodians) as engineering counterparts.
- Experience building or scaling a forward-deployed engineering function from early stage.
The base salary ranges included below will be commensurate with candidate experience, expertise and local market. Final offer amounts are determined by multiple factors, including candidate experience and expertise. At Galaxy, we maintain a total compensation philosophy which consists of a competitive base salary, annual bonus, and equity incentives. Base Salary Range $200,000—$260,000 USD.
About Galaxy Digital
Galaxy Digital is a technology-driven financial services and investment management firm providing institutions and direct clients with comprehensive solutions across the digital assets ecosystem. The company operates two main business segments: Digital Assets (offering trading, asset management, lending, and advisory services) and Data Centers (developing AI and high-performance computing infrastructure).