Head of Engineering

About the role

This Head of Engineering role at Xapo involves driving engineering excellence and predictability across the entire function. You will be responsible for setting and enforcing engineering standards, including code review practices and feedback loops, to ensure high-quality software delivery. A key aspect is owning the unified Software Development Life Cycle (SDLC) and ensuring all changes generate a regulator-ready audit trail, balancing compliance with development velocity.

The position requires significant people leadership, specifically managing and developing Engineering Managers. This includes performance management, growth, and overseeing the hiring process for the engineering function. You will also be accountable for the function's incident response, post-mortems, and the strategic roadmap for addressing technical debt, collaborating with solutions architects.

Success in this role means consistently meeting committed scope and dates, effectively clearing blockers, and integrating AI-first engineering practices where they genuinely add value. You will also ensure engineering aligns with quality, security, and architectural standards set by other departments, and manage engineering's capacity planning and OKR ownership.

The compensation for this position ranges from $120,000 to $200,000 USD.

Skills that matter here

• People Leadership: This role involves managing Engineering Managers, focusing on their performance, growth, and hiring across the function.
• SDLC Ownership: You will define and own the end-to-end unified Software Development Life Cycle for the engineering function.
• Delivery Predictability: A core accountability is ensuring the engineering function consistently ships committed scope on time, identifying and remediating shortfalls.
• Regulated Environment: The role operates within a regulated, Bitcoin-native context, requiring an understanding of compliance and risk management, especially for backend changes.
• AI First Engineering: You are accountable for driving the adoption of AI tooling in engineering, such as coding assistants and AI-assisted testing, to improve productivity.
• Distributed Systems: A solid understanding of backend distributed systems is required, particularly how to operate them in a high-stakes, regulated environment.

Who this role suits

• A leader with a proven track record of consistently meeting delivery commitments for an engineering organization.
• Someone who excels at developing and performance-managing other engineering leaders, not just individual contributors.
• An individual who can define and implement robust engineering practices, including SDLC, code review standards, and change management.
• A data-driven professional who uses metrics to drive action and improvement, rather than just reporting on them.

From the employer

• Delivery predictability across the engineering function - accountable for the function consistently shipping committed scope on committed dates, per tribe and function-wide. You own the practices that surface shortfalls early and the remediation that closes the gap.
• Engineering standards and practice - you set and enforce the engineering bar: code review standards, retrospectives, and the feedback loops that keep them healthy across the tribes.
• People management of Engineering Managers - performance management, growth, 1:1 cadence, and engineering hiring across the function. You are accountable for the EMs you develop and the standard they operate to.
• Unified SDLC ownership - you own and define the unified SDLC end to end. Engineering Managers run it day-to-day in their tribes.
• Backend change management - you own the governance of our deployment pipeline. You ensure 100% of changes generate a regulator-ready audit trail automatically, while designing a frictionless, risk-tiered approval process that subjects material changes to rigorous, formal review without gridlocking daily production velocity.
• AI-first engineering standard - accountable for driving genuine adoption of AI tooling across engineering: coding assistants, AI-assisted code review, and AI-assisted test generation as standard practice. You set the direction, decide where it adds real value versus where it doesn't, track adoption, and ensure teams get measurable productivity benefits - not tooling for its own sake.
• Blocker clearance - accountable for fast escalation and resolution of blockers, in-sprint and in engineers' backlogs. Blockers are surfaced early and cleared with discipline rather than allowed to age.
• Engineering incident response and post-mortems - own the engineering function's response to production incidents: timely escalation, structured post-mortem facilitation, and ensuring action items close.
• Tech-debt roadmap - own the function-level tech-debt roadmap: prioritising remediation, partnering with the Solutions Architect on architectural debt, and tracking progress against plan.
• Capacity planning - accountable for engineering capacity matching committed work; EMs execute the operational planning.
• Cross-department standard execution - implementing the quality framework defined by the Head of Quality Engineering, the security standards owned by Security, and the architecture standards agreed at the Architecture Advice Forum.
• Engineering OKR ownership - rolled up from Engineering Managers, with function-level accountability sitting here.
• Cross-functional initiative delivery - ensuring engineering does not become the blocker for initiatives spanning product, technology, and operational teams; coordinating on cross-division prioritisation and dependency management.

• 8+ years in software engineering, with at least 3–4 years in an engineering leadership role spanning multiple teams or squads - managing engineering managers, not just senior engineers.
• A track record of owning delivery predictability at function level: you have made commitments on behalf of an engineering organisation and built the practices to meet them consistently, without resorting to estimate-padding.
• Hands-on experience building and running engineering practice: SDLC definition, code review standards, change management, and the retro and feedback loops that keep them healthy.
• Strong people leadership - you have hired, developed, and performance-managed engineering managers and know what good EM execution looks like versus what needs intervention.
• A clear, evidence-based point of view on AI-assisted development across the SDLC - where it adds real value, and how to drive genuine adoption rather than dashboard adoption.
• Solid understanding of backend distributed systems and what operating them in a regulated, high-stakes environment demands: change management discipline, incident response, observability, and audit-readiness.
• Data-driven - comfortable owning engineering metrics (delivery predictability, cycle time, defect escape rate, blocker aging) and turning them into prioritised action rather than dashboards nobody acts on.
• Strong communicator across technical and non-technical audiences - you can write the SDLC definition, present the tech-debt roadmap to the CTO, and give an EM hard feedback, all with equal clarity.
• Experience in a regulated environment (fintech, banking, payments, or equivalent) with a real appreciation for what a quality or security failure means when customer funds are at stake.

• Impact Globally, Work Remotely.
• Shape the Future: Improve lives through cutting-edge technology, work 100% remotely from anywhere in the world.
• Great work-life balance: Build amazing things with a balance of autonomy and collaborative teamwork. Set your own work schedule and make use of a flexible PTO plan when you need to recharge.
• Expect Excellence: Collaborate, learn, and grow with a high-performance team. Learn how you learn best - from books to conferences, you’ll get a yearly budget for your individual learning and development goals.