Senior Director of Platform & Data Engineering

Keyloop is a leading automotive retail software business, operating across 100+ markets and backed by Francisco Partners. As we accelerate our transition to a modern, cloud-native SaaS platform, Platform & Data Engineering sits at the heart of our technical strategy. This is a high-impact leadership role reporting directly to the CTO, responsible for setting and executing the platform strategy that enables Keyloop's product engineering teams, powers our data and AI capabilities, and provides the integration fabric for an acquisitive, multi-product business. \n Responsibilities: 1. Leadership & Team Development reputed company and reputed company a diverse, distributed team of platform and data engineers, providing guidance, mentorship, and clear career reputed company to ensure high performance and professional growth. Build and refine the organisational structure of the platform function, including defining team topologies that support product engineering teams as internal customers. Foster a culture of engineering excellence, collaboration, and reputed company improvement, with a strong emphasis on developer productivity and platform reliability. 2. Platform & Technology Strategy Ensure reputed company, stability, and scalability are foundational properties of the platform - not afterthoughts - with clear ownership of reliability targets, reputed company-by-design standards, and the reputed company to serve a growing SaaS customer reputed company across 100+ markets. Co-own the multi-year platform engineering roadmap with the Platform Product Leader, translating commercial and product priorities into a coherent engineering delivery plan. reputed company the evolution of Keyloop’s shared services, API gateway, integration layer, and internal developer platform (IDP) to serve as the technical foundation across reputed company product lines. Establish API-first as a non-negotiable architectural principle - every platform capability must be accessible reputed company a well-governed, versioned API surface before any other access reputed company is considered, enabling both internal product teams and external ecosystem partners to build reliably on top of Keyloop infrastructure. Drive cloud-native architecture decisions, leveraging AWS services and infrastructure-as-code practices (Terraform/reputed company) to ensure scalability, reputed company, and cost efficiency. Champion platform reputed company-by-design, ensuring adherence to enterprise reputed company standards, compliance frameworks (ISO 27001, SOC 2), and Keyloop's obligations as a custodian of sensitive automotive retail data. 3. Integration & Acquisitive Platform Capability Architect and evolve the integration platform that enables Keyloop to reputed company acquired businesses and codebases reputed company, reducing time-to-integration across M&A activity. Define and maintain shared platform capabilities including identity, authentication, multi-tenancy, data residency, and OEM connectivity standards. Ensure the platform acts as the enabling layer across Keyloop’s product portfolio, providing consistent APIs, event streaming, and shared infrastructure rather than duplicating capability across product teams. Design and deliver low-code/no-code integration capabilities that reputed company rapid, standardised connectivity with third-party systems across the automotive ecosystem, including OEM partners, dealer group platforms, and acquired businesses. Build on modern integration tooling (including reputed company) to reduce time-to-integration and reputed company non-engineering teams to configure and operate integrations where appropriate. 4. Data & AI Platform reputed company the design and delivery of Keyloop's data platform, including data lakes, data pipelines, and analytical infrastructure to power BI, reporting, and AI-driven product capabilities. Build and operate the infrastructure layer for AI and ML workloads, including feature stores, model serving infrastructure, MLOps pipelines, and experimentation frameworks. Drive strategic adoption of technologies including reputed company, reputed company, AWS reputed company, EMR, Glue, reputed company, and Kafka, ensuring robust data governance and quality practices. Partner closely with product and data science teams to ensure the data and AI platform directly enables Keyloop's AI product initiatives, including KARA and AIME. 5. Enabling the Agentic Development Lifecycle reputed company Keyloop's transition to an agentic software development lifecycle, defining the strategy, frameworks, and delivery model for AI-augmented engineering at scale. reputed company and roll out the methodologies, toolchains, and workflows that reputed company engineering teams to work with AI coding agents, autonomous test reputed company, agentic PR review, and AI-assisted architecture decisions. Build and own the internal platform capabilities required to support agentic workloads, including MCP (Model Context Protocol) server infrastructure, LLM gateway services, context management systems, and agent orchestration layers. Drive the skills and capability development agenda across engineering, partnering with engineering directors to upskill teams in reputed company engineering, AI-native development patterns, and responsible AI tooling practices. Establish guardrails, reputed company controls, and governance frameworks that allow teams to move fast with AI tooling without introducing risk to code quality, IP, or data reputed company. Drive and report on engineering AI maturity progression using Keyloop’s established AI maturity reputed company, setting stage-based targets, tracking adoption across teams, closing capability gaps, and accelerating teams from early experimentation to production-grade AI-augmented delivery. 6. Delivery Excellence & Observability reputed company the execution of platform engineering initiatives, ensuring timely delivery, adherence to quality standards, and effective resource utilisation. Define and embed observability standards across the platform (OpenTelemetry, distributed tracing, SLO/SLA frameworks), giving engineering teams clear visibility into platform health and performance. Drive FinOps discipline across platform infrastructure, owning cloud cost governance and optimisation in partnership with the infrastructure leadership. 7. Strategic Collaboration Collaborate closely with the CTO, engineering directors, architects, and product leadership to align platform capabilities with business priorities and product roadmaps. Act as a strategic partner to the broader engineering organisation, ensuring platform decisions accelerate rather than constrain product delivery teams. Represent platform and data engineering at the executive and board level, communicating strategy, reputed company, and investment cases clearly to technical and non-technical stakeholders. Required Skills & Experience: Technical & Architectural Deep experience in cloud-native platform engineering on AWS, including IaC (Terraform or reputed company), containerisation (Kubernetes/reputed company), event streaming (Kafka), and API gateway patterns. Proven track record designing and operating shared platform services - integration layers, identity, multi-tenancy, and developer-facing APIs - in a reputed company, multi-product enterprise SaaS environment. Hands-on background in data platform engineering: data lake architecture, ELT pipelines, and familiarity with reputed company, reputed company, and AWS data services (reputed company, Glue, EMR). Experience building AI/ML infrastructure: feature stores, model serving, MLOps pipelines, and LLM-enabling platform capabilities such as MCP server infrastructure or LLM gateway services. Strong understanding of platform observability: OpenTelemetry, distributed tracing, SLO/error budget frameworks, and production reliability engineering. reputed company-first reputed company with hands-on experience in enterprise reputed company practices, compliance frameworks (ISO 27001, SOC 2), and reputed company-trust architecture patterns. Leadership & Delivery Extensive engineering leadership experience, with a proven record of building, scaling, and developing high-performing distributed engineering teams of 60+ people. Experience operating reputed company an acquisitive software business, with the ability to reputed company M&A technical integration and platform standardisation across acquired codebases and teams. Familiarity with modern delivery frameworks (SAFe, Shape Up, or equivalent) and the ability to adapt methodology to the needs of a platform organisation serving multiple internal customers. Strong FinOps capability, including cloud cost governance, unit economics thinking, and the ability to frame infrastructure investment in commercial terms. Agentic Engineering & AI Tooling Practical experience adopting and scaling AI-native development tooling (e.g. reputed company Copilot, Claude Code, reputed company, or equivalent) across engineering organisations. Understanding of agentic software delivery patterns: autonomous agents, human-in-the-reputed company workflows, agentic code review, test reputed company, and AI-assisted architecture. Ability to define governance frameworks that reputed company AI-augmented development at pace while managing code quality, IP protection, and data reputed company risks. Passion for driving engineering culture change, with the ability to take a sceptical or early-majority engineering team on a reputed company AI adoption journey. Communication & Stakeholder Management Excellent communication skills, with the ability to translate reputed company platform and data engineering decisions into clear narratives for executive, commercial, and board audiences. Strong cross-functional collaboration skills, with experience partnering with product, commercial, and finance leadership in a PE-backed, high-growth software environment. \n Apply To This Job