• Design, develop, and maintain SAP CAP services and applications using Node.js or Java • Build and expose APIs using OData (primarily v4) and REST • Define and implement CDS data models, service layers, and business logic • Develop CAP based extensions aligned to S/4HANA clean core principles • Troubleshoot complex issues across CAP services, data models, and integrations • Ensure performance, scalability, and maintainability of CAP solutions • Act as the technical lead for SAP CAP components within projects • Define CAP development standards, patterns, and best practices • Review solution designs, code, and pull requests for quality and consistency • Guide and mentor junior developers in CAP concepts and delivery practices • Lead by example through hands on coding and problem solving • Design CAP services that integrate with S/4HANA and external systems • Implement synchronous and asynchronous integration patterns where required • Collaborate with BTP, Integration, and Architecture specialists (where applicable) • Support end to end application design from CAP services through to consumers (UI or integrations) • Participate in technical workshops and solution design discussions • Translate business requirements into CAP focused technical solutions • Provide estimates, delivery input, and technical risk assessment • Communicate clearly with stakeholders on CAP design and delivery decisions

• Develop, deploy, and maintain Real-Time Operating System and hypervisor configurations for Safety-Critical applications. • Leads and/or contributes to activities to develop, document and maintain architectures, requirements, algorithms, interfaces and designs for software systems. • Develops code and integrates complex software components into a fully functional software system. • Contributes to hypervisor (i.e. Xen) deployment, configuration, and integration for safety-critical partitioned environments. • Supports runtime maturation efforts including performance analysis, determinism validation, and reliability improvements. • Develops software verification plans, test procedures and test environments, executing the test procedures and documenting test results to ensure software system requirements are met. • Provides technical leadership for software projects.

• Architect the future version(s) of our key systems like databases, distributed jobs and many others, while taking into account our scaling needs. • Design and implement developer tooling that makes development and deployments safer, reproducible, and easy to rollout. • Drive excellence in observability and monitoring while guiding incident response to ensure issues are resolved quickly and we build a great on-call experience. • Collaborate with engineering teams to maintain a high level of technical quality across our systems while addressing debt, upgrades and platform improvements. • Mentor engineering on how to design reliable, fault-tolerant systems and easy-to-use runbooks for when things go wrong.

• Build AI-powered marketing infrastructure • Design and operate AI agents that run marketing workflows autonomously — including lead enrichment, campaign personalisation, content production, and signal monitoring • Build experimentation infrastructure that tests messaging, channels, and sequences faster than traditional marketing teams thought possible • Create self-improving systems with evals, feedback loops, and guardrails that get better without constant supervision • Build and optimise outbound engines using Clay, Apollo, RB2B, Unify, Instantly, and similar tools • Surface buying signals (hiring, funding, competitor moves, contract renewals) and route them to sales with full context • Design enrichment workflows that prioritise accounts automatically and identify warm intro paths • Own lifecycle marketing: nurture sequences, re-engagement campaigns, and credit consumption alerts that drive expansion • Run 1:many ABM campaigns targeting industry marketing account lists • Build and iterate on paid campaigns (LinkedIn, Google, Reddit) with rapid A/B testing • Own experimentation velocity: run 4–6 marketing experiments per month with clear hypotheses, metrics, and iteration cycles • Document what works and systematise successful experiments into repeatable playbooks • Track pipeline influence, reply rates, meetings booked, and cost per meeting across all channels