Engineering Manager - Remarketing

• A minimum of 8 years in software engineering, including at least 3 years in engineering management or an equivalent leadership role.

• Proven experience managing and developing multidisciplinary software-engineering teams.

• Demonstrated success delivering and operating complex SaaS or cloud-based products in production.

• Experience leading modernization, legacy reduction, or platform evolution while continuing to deliver customer value.

• Experience improving software quality, SDLC discipline, automated testing, release governance, and operational reliability.

• Strong cloud and modern DevOps experience; AWS experience is preferred.

• Experience managing customer-impacting incidents, cross-team dependencies, and critical technical escalations.

• Experience in automotive software, digital marketplaces, image processing, mobile products, or AI-enabled products is advantageous but not required.

• Fluent English is mandatory; French is a plus.

• Strong analytical, organizational, and problem-solving abilities.

• High ownership, sound judgement, and effectiveness under ambiguity.

• Constructive assertiveness and confidence to challenge unrealistic commitments or incomplete inputs.

• Collaborative leadership with strong negotiation and cross-functional skills.

You will operate as the engineering owner for the Remarketing domain, partnering with Product on roadmap execution while maintaining clear accountability for engineering capacity, delivery, quality, technical sustainability, and team development. Success requires a builder and change-agent mindset: creating clarity, strengthening ownership, improving the operating model, and helping the team deliver valuable outcomes with greater predictability and confidence.

As Engineering Manager for Remarketing, you will lead an multidisciplinary engineering team of approximately eight people, potentially organized across multiple delivery streams responsible for a complex portfolio of customer-facing mobile and web applications, backend services, integrations, quality capabilities, and AI-enabled image-processing workflows. Reporting to the Director of Engineering, you will be accountable for team development, engineering execution, delivery predictability, quality, and technical sustainability.

You will partner closely with Product, the Technical Lead, QA, Architecture, DevOps, Customer Success, Professional Services, and other engineering teams. Product owns the vision, roadmap, and the what and why; you own engineering capacity, delivery planning, and feasible execution of the when and how. You will challenge incomplete requirements, ensure work is ready before commitment, and make risks, dependencies, and trade-offs transparent.

This is a technically credible leadership role rather than a full-time coding position. You must be able to review designs, challenge architectural decisions, guide engineers and the Technical Lead, and enter the code or production diagnostics when necessary.

This role requires a change-oriented leader who can improve the operating model while maintaining delivery and production continuity across a complex product landscape.

Team Leadership and Development

• Lead, coach, and develop a high-performing multidisciplinary team of approximately eight people, including internal engineers and external contributors.

• Conduct regular one-to-one meetings, provide timely feedback, manage performance, and create career-development plans.

• Own hiring, onboarding, capability planning, career development, continuity planning for critical roles, and recommendations related to progression.

• Strengthen the Technical Lead role and clarify accountability across Engineering, Product, and QA.

• Foster ownership, collaboration, psychological safety, continuous learning, and constructive challenge.

• Be accountable for engineering execution and delivery predictability across the Remarketing scope.

• Translate roadmap priorities into realistic delivery plans based on capacity, dependencies, risks, technical constraints, and operational workload.

• Provide high-level estimates and estimated delivery dates, revising them transparently as scope or evidence changes.

• Own sprint planning, execution control, reviews, retrospectives, refinement facilitation, capacity planning, and continuous improvement.

• Protect the team from uncontrolled scope changes and ad hoc requests, ensuring accepted work is visible, prioritized, and traceable in Jira.

• Manage cross-team dependencies, release readiness, and scope-versus-timeline trade-offs.

• Use engineering and delivery metrics to reduce carry-over, improve flow, and communicate progress and risk.

• Operate under a clear model: Product defines the what and why; Engineering owns feasible execution of the when and how.

• Challenge unclear requirements and ensure initiatives meet agreed Definition of Ready standards before commitment.

• Contribute engineering input to discovery, functional analyses, RFCs, roadmap feasibility, non-functional requirements, and sequencing.

• Partner with Product to ensure that roadmap items are translated into delivery-ready epics, with clear scope, acceptance criteria, dependencies, risks, and intended outcomes, before Engineering commits to execution.

• Work with Customer Success, Professional Services, PMO, Sales, and Support through agreed channels and explicit ownership boundaries.

• Participate in customer interactions only exceptionally, primarily for critical technical escalations.

• Drive a disciplined and traceable SDLC, with Jira as the source of truth for engineering execution.

• Establish and enforce Definitions of Ready and Done, release criteria, quality gates, and consistent issue-type usage.

• Ensure that the team implements an appropriate automated-testing strategy across the relevant test levels, in partnership with the Technical Lead and QA.

• Be accountable for integrating security, reliability, observability, performance, and operability into engineering planning and execution, in collaboration with the relevant specialist teams.

• Own engineering participation in incident response, root-cause analysis, bug triage, corrective actions, and post-release monitoring.

• Balance roadmap delivery, defects, operational support, technical debt, and modernization.

• Review solution designs, challenge architectural choices, and guide decisions with the Technical Lead and Architecture.

• Provide organizational leadership for modernization initiatives, partnering with the Technical Lead and Architecture on technical direction and execution.

• Ensure that technical decisions across distributed systems, APIs, mobile and web applications, data stores, integrations, and asynchronous workflows are appropriately reviewed and owned.

• Champion SOLID principles, clean and modular architectures, pragmatic domain-driven design, secure engineering, and useful documentation.

• Ensure technical debt is understood, connected to business impact, and transparently discussed with Product.

• Support the responsible integration of AI-enabled capabilities and external AI services without requiring specialist model-development expertise.

• Lead the team in operating cloud workloads, preferably on AWS, with sound decisions on scalability, resilience, security, cost, and service ownership.

• Drive effective CI/CD, infrastructure automation, release management, environment strategy, and rollback practices.

• Use logging, metrics, tracing, alerting, and service-level indicators to improve system health.

• Ensure services and integrations meet the availability, resilience, recovery, security, and documentation requirements appropriate to their business criticality.

• Strong people management, coaching, hiring, performance management, conflict resolution, and stakeholder communication.

• Proven ability to develop senior engineers and Technical Leads and manage mixed internal and external teams.

• Demonstrated ownership of delivery, capacity planning, dependencies, release planning, and risk management.

• Ability to create clarity and make difficult scope, capacity, and priority trade-offs.

• Strong command of Agile and lean principles without treating ceremonies as a substitute for outcomes.

• Business-oriented mindset connecting technical decisions to customer value, quality, cost, and operational impact.

• Strong software-engineering foundation and recent experience leading distributed, customer-facing cloud systems.

• Experience with architecture and modernization across APIs, backend services, web and mobile applications, databases, and integrations.

• Strong experience operating cloud workloads, preferably on AWS, combined with practical knowledge of containers, CI/CD, observability, security, reliability, and production operations.

• Technology-stack agnostic, with the ability to lead environments that may include.NET, React/Next.js, Flutter, and legacy technologies.

• Strong understanding of automated testing, quality gates, secure SDLC practices, and maintainable software design.

• Ability to lead a team integrating AI-enabled capabilities and external AI services, without requiring specialist model-development expertise.