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Über
Founded over 16 years ago, with more recent investments from Accel-KKR, Entersekt is a leader in digital banking fraud prevention and payment security, including mobile authentication, mobile app security, and 3-D Secure authentication for issuers, acquirers and payment networks. We offer highly scalable products with a track record of success across multiple continents. Entersekt enables secure digital transactions for leading financial institutions globally. We exist to create a world where everyone can transact digitally without fear or compromise. Currently, we protect the digital transactions of over 210 million active users on our platform and hold 120 active patents that recognize innovation in digital security, payments, and user experience. Entersekt offers customers secure authentication and digital payments experiences that remove unnecessary friction. Entersekt has a diverse product portfolio and aggressive roadmap that positions the company well to sustain competitive advantage as it expands globally with emphasis on North America and European markets. The Ideal Candidate
You're a senior engineering leader who has modernized software delivery at scale and knows how to drive consistent engineering excellence across multiple product teams. You've led transformations involving CI/CD, test automation, progressive delivery, AI-enabled engineering practices, and cloud-native architectures. You're comfortable influencing a matrixed organization, setting standards, and guiding POD leaders without direct line authority. You balance engineering rigor, risk management, and speed, while partnering closely with Product, Architecture, Security, and Platform Engineering. You enjoy driving clarity, structure, and governance in environments that are scaling quickly, and you have a strong track record of bringing consistency to engineering processes while enabling innovation and autonomy. The Role
The VP of Software Engineering is accountable for enterprise-wide engineering standards, release governance, toolchain strategy, and AI-driven engineering transformation across our product development PODs. This role serves as the central owner of the SDLC, quality gates, metrics, release patterns, architectural governance, and engineering operating model. It drives alignment across PODs without initially taking direct line management of engineering team leads, but with clear authority to define, enforce, and continuously improve engineering practices. You will partner closely with POD Leaders, Product, Architecture, SRE/Platform Engineering, Information Security, and GRC, ensuring our products meet high standards of reliability, security, compliance, and delivery consistency, all while embedding modern engineering practices across the SDLC. Responsibilities
Cross-Functional Leadership
Operate as a matrixed leader: influence POD Leaders, Product Management, Architecture, SRE/Platform, and InfoSec; chair an Engineering Standards Council to ratify and evolve practices. Budget for and govern vendor relationships and tooling investments; establish business cases for modernization.
Engineering Governance & Standards
Define, publish, and enforce the enterprise SDLC and development standards (branching, code review, secure coding, documentation), including POD consistent Jira workflows, states, and entry/exit criteria from ideation through production. Establish Definition of Ready/Done for features and defects; set predevelopment conditions of success expected from Product before work begins. Create quality gates (unit, component, functional, nonfunctional) and observability baselines and ensure they are uniformly applied across PODs. Define, monitor, report, and implement strategies to continuously improve software engineering and delivery metrics (e.g., FLOW, DORA).
Release & Deployment Management
Institutionalize separation of deployment from release to reduce risk and improve flexibility; standardize feature flag usage, canary, and progressive delivery patterns, and kill switches for rapid rollback. Codify roles: Engineering ensures predictable, automated deployments; Product owns feature exposure decisions and business rollout strategy. Align with ITIL 4 guidance that treats Release and Deployment as distinct practices with different objectives.
Quality Engineering & Test Automation
Lead the shiftleft transformation so software developers own unit, component, and functional tests within PODs; QA evolves to enablement, tooling, and governance. Oversee automation frameworks, self-service test platforms, and AI assisted test generation, flakiness detection, and impact analysis in CI/CD. Directly manage the Quality Manager and scale a small excellence function to drive consistency, training, and audits.
AI-Driven Engineering Transformation
Build an AI adoption roadmap across the SDLC: AI assisted coding & reviews, test generation, defect triage, vulnerability remediation, documentation, and intelligent planning/estimation; implement guardrails for privacy, security, and provenance. Partner with Platform/SRE to embed AI augmented developer experience and insights into internal developer portals and pipelines.
Compliance, Security & Risk
Embed securebydesign practices and evidence collection to meet SOC 2 Criteria and PCI DSS/3DS requirements; leverage control overlaps to streamline audits and reduce burden. Partner with Cybersecurity/GRC to ensure policy?control?evidence alignment in code scanning, dependencies, secrets management, and change control.
Architecture Governance & Enablement
Define and enforce architectural standards for scalable, secure, and compliant systems across PODs. Partner with Principal Engineers, Lead Engineers, Platform Engineering, and Security to ensure cloud-native, API-first, and secure-by-design principles are embedded in all product lines. Support POD-level autonomy while ensuring architectural decisions align with enterprise patterns and compliance requirements (e.g. SOC 2, PCI DSS, PCI 3DS). Leverage AI tools to assist with architectural documentation, impact analysis, and dependency management.
Authority & Decision Rights
Approve and enforce the enterprise SDLC, Jira workflows, and quality gates. Approve standards and block releases that fail to meet defined engineering gates or compliance requirements. Own toolchain standards (GitLab/Jira/Confluence/Jellyfish) and require corrective actions for noncompliant usage. Set policy for feature flag governance (naming, lifespan, cleanup) and progressive rollout patterns.
Successful candidates for this role will generally possess the following qualifications and skills: 10+ years in software engineering with 5+ years in senior leadership roles in SaaS, platform engineering, or large-scale product organizations. Proven experience influencing matrixed teams and driving engineering transformation. Demonstrated success modernizing engineering practices (CI/CD, progressive delivery, observability). Hands-on experience with GitLab-based secure CI/CD and Jira-integrated planning at scale. Deep understanding of engineering intelligence and metrics-driven leadership (including DORA). Experience in compliance-heavy environments such as fintech or authentication. Practical experience applying secure-by-design practices in regulated or audited contexts. Track record implementing AI-enabled engineering practices. Training or experience in Agile, DevOps, Architecture, or ITIL is advantageous. Success measures (1218 months): Engineering Governance:
A single, documented SDLC with POD consistent Jira workflows, entry/exit criteria, and quality gates is adopted across all products; audit-ready by design. Progressive Delivery:
Separation of deployment and release is standardized with feature flag governance and stagegated rollouts (internal ? % canary ? full), with clear responsibilities between Product (release decisions) and Engineering (deployment reliability). AI Enabled SDLC:
AI assists coding, testing, planning, and documentation; measurable cycletime improvements and reduction in toil are achieved responsibly and securely. Toolchain & Metrics:
GitLab, Jira, Confluence, and Jellyfish are standardized and integrated for traceability and engineering intelligence; DORA metrics dashboards report lead time, deployment frequency, change failure rate, and time to
Sprachkenntnisse
- English
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