Director, AI & Automation – Shared Services

Who We Are Looking ForWe are hiring a Director AI & Automation - Shared Services to build and scale AI-enabled efficiency across Finance HR Legal and Marketing. This is a player-coach role: you will be expected to personally design and deliver automation and AI solutions while also owning the operating model (intake prioritization governance and benefits tracking).In the first 6-12 months you should expect to spend a significant portion of your time building (coding configuring automations integrating systems and hardening solutions for production). You will have the opportunity to recruit an AI Automation Engineer after you start; however this role requires hands-on technical depth from day ideal candidate will exhibit the ability to maintain a high-level of confidentiality organisation attention to detail initiative autonomy and judgment as well as an ability to effectively prioritize workflow and execute assignments. This is a dynamic role that requires responsiveness and comfort working in a fast-paced this role success is measured by outcomes and adoption not experimentation for its own sake: 15-30% cycle-time reduction on targeted processes with manual touches and exception rates reducedHigh adoption and sustainable change (target: >80% adoption in pilot groups where appropriate)Audit-ready controls embedded (e.g. access control audit logging evidence trails and documented SOPs)Benefits realized and reported quarterly (hours returned annualized net benefits quality and risk reductions)Dual OKRs: business outcomes (cycle time hours returned adoption audit findings) and platform outcomes (reliability/SLA cost per run zero privacy incidents) in partnership with IT SolutionsThis role can be based at our offices near London Bridge or Bournemouth with 2-3 days in the officeWhat You Will Work OnHands-on build and delivery (primary)Identify prototype and ship AI and automation solutions from discovery through MVP and scale (LLM workflows RPA workflow automation integrations and lightweight internal apps)Write production-quality code where needed (primarily Python) and build reliable integrations (APIs webhooks ETL-style data movement document pipelines)Design and implement LLM-powered features such as document intake/summarization classification and routing knowledge retrieval exception handling and agent-assisted operations - with clear quality gates and evaluationBuild automation that fits real operating constraints: retries idempotency monitoring/alerts and clear ownership for ongoing supportCreate and maintain reusable building blocks (templates libraries prompt/eval harnesses connectors) to accelerate delivery across use casesPortfolio ROI and governance (shared services leadership)Own the use-case intake process prioritization rubric and shared backlog across Finance HR Legal and MarketingRun a joint weekly backlog review with IT Solutions to align on capacity dependencies and delivery sequencingBaseline current-state metrics (cycle time effort error rates) and build business cases with clear assumptions and benefits trackingProvide monthly steering updates (progress risks decisions needed) and quarterly benefits reportingCoordinate UAT and rollout with process owners; ensure SOPs training materials and controls documentation are updated for sustainable adoptionControls-first delivery with IT SolutionsPartner with IT Solutions to design solutions that meet security and platform guardrails (SDLC identity/RBAC secrets management data protection and change control)Implement definition-of-done gates for AI automation releases: threat model RBAC audit logging evaluation/red-team results as applicable rollback plan runbooks and observabilityCoordinate with IT change control processes (e.g. CAB) where required and ensure releases are supportable with clear ownership and monitoringEnsure vendor/tooling choices and data flows are compliant with relevant policies and regulations (e.g. SOX controls where applicable GDPR/data privacy requirements)Team building and capability developmentRecruit mentor and lead additional capacity (e.g. an AI Automation Engineer) as the portfolio scales; set standards for code quality and delivery hygieneBuild strong working relationships across Shared Services and IT creating clear handoffs and support models (who owns what post-launch)Drive practical enablement for teams: patterns documentation and best practices to increase automation literacy and adoptionExample focus areasFinance: AP/AR workflows month-end close support reconciliations invoice and payment exception handlingHR: case intake and routing employee request workflows knowledge retrieval for standard policy questionsLegal: contract intake clause classification triage and workflow routing obligation tracking supportMarketing: content operations support approvals workflows internal reporting and request handlingDay PlanFirst 30 daysAlign on an operating agreement (capacity intake/backlog decision rights and definition-of-done / release gates)Baseline metrics for priority processes; stand up repos logging and an evaluation harness for AI featuresDeliver a short list of MVP candidates with business cases and delivery plansBy 60 daysShip 2-3 MVPs through the full security/evaluation pipeline and into pilot groupsPublish the first KPI dashboard for adoption and benefits trackingEstablish a repeatable delivery pattern (templates runbooks monitoring and support model)By 90 daysScale at least one MVP (broader rollout hardened operations and measurable benefits)Tune reliability and delivery throughput (SLOs definition-of-done backlog capacity planning)Finalize hiring plan and begin recruiting additional engineering capacity as neededWho You Will Work WithSVP Finance (initial direct manager) to set priorities remove roadblocks and track benefits like a P&LProcess owners across Finance HR Legal and Marketing to define requirements run UAT and drive adoptionIT Solutions to align on architecture integrations security controls platform guardrails and supportabilityOptimization / Business Systems partners to coordinate process redesign and change management where neededWhat You Will BringExperience leading platform decisions across automation ecosystems and deploying scalable solutionsProven experience delivering automation and AI solutions in an enterprise environment (MVP through production)Strong hands-on engineering skills with high proficiency in Python for APIs integrations and AI-driven workflowsExperience with enterprise LLM platforms (e.g. Azure OpenAI AWS Bedrock Google Vertex AI Anthropic Claude)Experience implementing LLM-based solutions (prompting retrieval-augmented generation tool/function calling document processing and evaluation/quality testing)Experience with workflow automation and/or RPA platforms (e.g. UiPath Microsoft Power Automate Automation Anywhere ServiceNow workflows) or equivalent automation experienceSolid software engineering fundamentals: version control testing code review packaging CI/CD concepts and documentationFamiliarity with modern data platforms and pipelines (e.g. Databricks Snowflake Palantir Foundry Airflow Kafka)Experience deploying solutions on cloud platforms (Azure AWS or GCP) with containerization and CI/CD toolingComfort partnering with security and IT to design controls: identity/RBAC secrets management audit logs and change controlAbility to translate ambiguous business problems into shipped solutions; strong stakeholder communication skillsExperience working cross-functionally with business teams and driving adoption (training rollout planning and SOP updates)PreferredExperience in Shared Services Global Business Services finance operations or other back-office process transformation rolesWorking knowledge of Go and/or TypeScript for building services or lightweight internal tools; willingness to learn new stacks as neededExperience building monitoring/observability (metrics logs tracing) and operating production servicesExposure to risk compliance audit or regulated environments; ability to design evidence trails and control documentation