Head, Engineering

Aboitiz Data Innovation (ADI), the Aboitiz Group's Data Science & AI Center of Excellence, is building cloud‑native data platforms, AI solutions, and GenAI‑powered products for internal- and external-facing deployment across a variety of sectors. We believe data can drive change for a better world by advancing businesses across industries and communities.

We are looking for a Head of Engineering to oversee and guide the strategic direction of an organization's engineering efforts, ensuring that engineering initiatives align with the company's overall objectives and drive innovation. Reporting to the Chief Technology & Operating Officer (CTOO), the Head of Engineering will be tasked to drive the overall Data Science and Technology strategy and execution acting as both a subject matter and business export, making decisions that will impact the current and future operations of the organization—driving scalable delivery, operational excellence, and rapid time‑to‑value.

If you are excited to work in a fast-paced start-up environment, this role will provide a great opportunity to grow your career with us. 

Responsibilities

• Engineering Vision, Architecture Governance & Technical Strategy
  • Establish and clearly communicate a compelling engineering vision and technology roadmap aligned with business and product objectives in collaboration with the CTOO.
  • Stay abreast of emerging technologies, industry trends, and best practices to drive innovation and maintain a competitive edge.
  • Review, approve, and coach solution, data, and ML architectures (AWS, Azure, Databricks Lakehouse).
  • Maintain reference architectures, enforce design‐for‑cost, security, and reliability principles.
• Product Roadmap Co‑ownership
  • Translate product vision into engineering epics, milestones, and capacity plans.
  • Balance new features, technical debt, and non‑functional requirements; manage build‑vs‑buy decisions.
• Agile Engineering Excellence & Continuous Improvement
  • Embed Scrum/Kanban, CI/CD, DevSecOps, and MLOps; adopt DORA & Accelerate metrics.
  • Implement SRE practices and incident management playbooks.
  • Drive continuous improvement of engineering processes, tools, and technologies to enhance velocity, quality, and developer experience.
• Talent, Capacity & Budget Management
  • Lead, mentor, and scale a 20 + FTE multi‑disciplinary org; implement career ladders, training programmers, and succession plans in collaboration with our Talent team.
  • Oversee the allocation of engineering resources, budgets, and project timelines to ensure optimal utilization and on‑time delivery.
  • Own engineering OPEX and recommend CAPEX tooling/cloud investments.
• Governance, Security & Compliance
  • Ensure ISO 27001, DPA, SOC 2 compliance via shift‑left security and privacy‑by‑design.
  • Champion data governance, lineage, and quality frameworks in collaboration with our Data Governance team.
• Delivery, Reliability & Cost KPIs
  • Improve deployment frequency, lead time, change‑failure rate, uptime, and cloud‑cost efficiency.
  • Publish engineering scorecards to execs and boards.
• Stakeholder & Client Engagement
  • Represent engineering in sales pursuits, customer demos, audits, and investor due‑diligence.
  • Collaborate with Product, Design, and GTM teams to ensure seamless delivery and feedback loops.
• Vendor & Partner Management
  • Evaluate, negotiate, and manage cloud/SaaS and staffing vendors against budget and SLAs, in collaboration with our Vendor Management team.
• Culture of Continuous Innovation
  • Foster an environment of experimentation and learning, encouraging teams to prototype, test, and adopt new technologies.
  • Drive PoCs in GenAI (LLMs, RAG, vector DBs), data‑mesh, and developer‑experience tooling into production. Evaluate and introduce new architectural concepts and frameworks, and recommend adoption where applicable.

Requirements

• Bachelor's or Master's Degree in Information Technology, Data Science, or related disciplines
• 8+ years of extensive experience in Engineering/ AI and/or Data Science field with 2 or more years in a senior management capacity managing multiple teams
• Proven ownership of cloud operations (AWS and/or Azure) and Databricks or equivalent lakehouse deployments.
• Track record instituting Agile, CI/CD, DevSecOps, SRE, and MLOps practices.
• Deep knowledge of data‑privacy and security standards (ISO 27001, GDPR/SOC 2).
• Exceptional stakeholder communication and vendor‑negotiation skills.
• Proven leadership skills and experience managing diverse engineering teams.
• Strong technical knowledge across various engineering disciplines. In-depth knowledge of engineering principles, practices, and industry standards
• Good knowledge of best practices in fields of AI and Data Science
• Strong written and verbal communication skills to convey technical concepts to both technical and non-technical audiences. 
• Ability to drive strategic initiatives and manage complex projects.
• Analytical and problem-solving skills to navigate complex technical challenges.

Reporting & Stakeholders

• Reports to: CTOO
• Direct reports: Engineering Managers / Leads for Data Engineering, Software Engineering (front‑end, back‑end, full‑stack), UI/UX, BI & Analytics, Cloud/DevOps/DevSecOps, and MLOps
• Key stakeholders: CEO, Head of Delivery (Product & Sales), Head of Corporate Services, internal and external customers