Director of Engineering

At
Transnetwork
, we are an innovative company in the field of remittances, committed to excellence and the development of effective financial solutions. Our work environment is dynamic, collaborative, and focused on continuous learning, where we support the growth and development of each of our employees.

We are seeking an accomplished engineering leader to scale and mature a high-performance technology organization across multiple product lines and platforms. The ideal candidate is a strategic, hands on leader who excels in building and guiding modern engineering teams, driving delivery excellence, and partnering cross functionally to execute an ambitious product and technology roadmap. This role oversees multiple development squads and technical domains, ensuring quality, velocity, reliability, and innovation across the engineering portfolio

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About the Job

• 10+ years of progressive software engineering leadership experience
• Proven success leading multi-squad, multi-platform engineering tea
• Demonstrated experience implementing AI to enhance development processes, such as using LLMs for code generation/review, AI-driven test automation, predictive maintenance, or developer productivity analytics
• Deep experience with Agile product delivery models and squad-based team structures
• Strong background in distributed systems, cloud platforms (AWS / Azure / GCP), and modern development stacks
• Demonstrated ability to scale engineering organizations and develop technical talent
• Excellent communication and stakeholder management skills; ability to present to senior executives and board.

Prefered

• Experience in fintech, payments, SaaS, or mission-critical transaction platforms
• Experience with microservices, event-driven architecture, and platform modernization programs
• Hands-on experience leading AI integration in engineering workflows (e.g., GitHub Copilot Enterprise, custom AI agents, or ML-based DevOps tools)
• Familiarity with data, ML/AI engineering practices, and real-time data environments
• Experience leading distributed global engineering teams
• DevSecOps and regulatory environment exposure (PCI, SOX, SOC2, etc)

Traits & Leadership Competencies

• Strategic systems thinker with strong execution discipline
• Customer-centric mindset with commitment to product-driven value delivery
• Inspiring leader skilled in talent development and organization design
• Bias toward action, outcomes, simplification, and AI-enabled innovation
• Collaborative, transparent, and highly accountable

Leadership & Strategy

• Lead, mentor, and scale multiple cross-functional engineering squads spanning diverse technologies, products, and regions
• Define and execute engineering strategy aligned to business and product goals
• Integrate AI-driven tools and methodologies to accelerate development cycles, enhance code quality, and optimize team productivity (e.g., AI-assisted code generation, automated testing, predictive analytics for risk and performance
• Build a culture of high performance, accountability, continuous learning, and technical excellence
• Own engineering workforce planning, hiring, and career development pathways
• Champion modern engineering practices including Agile, DevSecOps, automation, and cloud-native delivery

Execution & Delivery

• Drive delivery of complex multi-platform features and initiatives across squads, ensuring quality, predictability, and rapid time-to-value.
• Establish engineering KPIs and performance metrics (including DORA / Agile delivery metrics, and AI utilization effectiveness metrics)
• Ensure successful execution of modernization, platform consolidation, and/or microservices initiatives where applicable
• Partner closely with Product, Architecture, DevOps/SRE, InfoSec, and QA to ensure cohesive execution and shared success metrics.

Technology & Architecture

• Provide architectural guidance and engineering governance across services, applications, and integrations
• Enforce scalable, secure, and maintainable engineering standards
• Advocate for and implement cloud-native, API-first, and high-availability architectures
• Promote adoption of AI-enhanced tools for architectural reviews, threat modeling, code optimization, and system design validation
• Drive continuous improvement in code quality, observability, reliability, and platform resilience

Operational Excellence

• Enhance engineering processes, playbooks, and lifecycle maturity
• Ensure robust release engineering practices, CI/CD automation, AI-powered pipeline optimization, and infrastructure-as-code adoption
• Oversee vendor/partner engineering resources when aplicable
• Manage engineering budgets, tooling investment, and resource allocation