Development Expert

SAP; London; On-site; GBP 80,000 - 120,000; Full time

Job summary

A leading enterprise software company in London seeks an experienced professional to architect and lead AI-powered automation platforms. The role involves designing Kubernetes-based solutions, enhancing enterprise procurement processes, and promoting cloud-native practices. Candidates should have significant experience in platform architecture, various programming languages, and an understanding of modern DevOps practices. The position offers opportunities for constant learning and skill growth in a diverse work environment.

Benefits

Constant learning opportunities

Skill growth and development

Great benefits

Qualifications

• Experience with AI-enabled platforms and cloud-native systems.
• Demonstrated reductions of multi-hour pipelines to sub-30 minutes.
• Strong understanding of security and compliance for AI.

Responsibilities

• Architect and lead AI-powered engineering productivity platforms.
• Implement strategies for dynamic tool discovery and framework design.
• Build domain-aware knowledge graphs and optimize resource management.

Skills

Strategic Technology Leadership

Polyglot Engineering: Java/JVM, Go, Python

Enterprise Integration Mastery

Cloud-Native at Scale

DevOps Excellence

Education

10–15+ years overall experience

7–10+ years in platform/architecture leadership

Tools

Kubernetes

Grafana

Jenkins

Job description

Overview

We help the world run better. At SAP, we keep it simple: you bring your best to us, and we\'ll bring out the best in you. We\'re builders touching over 20 industries and 80% of global commerce, and we need your unique talents to help shape what\'s next. The work is challenging – but it matters. You\'ll find a place where you can be yourself, prioritize your wellbeing, and truly belong. What\'s in it for you? Constant learning, skill growth, great benefits, and a team that wants you to grow and succeed.

Summary: You’ll join the SAP Procurement Engineering organization within our Intelligent Spend Management group, contributing to transforming how enterprises manage their procurement processes.

Responsibilities

• Architect and lead an enterprise-grade, AI-powered engineering productivity and DevOps automation platform that combines agentic copilots, conversational workflows, intelligent orchestration, and continuous learning tailored to SAP’s procurement domain.
• Establish intelligent test selection and change-impact analysis at portfolio scale to compress multi-hour pipelines to minutes, increase throughput, and materially reduce cloud spend without sacrificing quality.
• Design and implement Kubernetes operators/CRDs for ephemeral environment provisioning, parallel test execution, and elastic scaling that optimize utilization while ensuring isolation and reliability.
• Build a secure framework for dynamic tool discovery, capability negotiation, and policy-aware routing (MCP-like), enabling AI agents to safely invoke internal systems, APIs, and automations.
• Deliver IDE/terminal assistants and intelligent web interfaces that understand repo/terminal context, retain cross-session memory, and support multi-modal interaction, driving daily adoption and measurable productivity gains.
• Introduce natural-language workflow creation with predictive optimization and cross-organizational learning; integrate with enterprise automation (e.g., n8n/Temporal/GitOps) to convert tribal knowledge into repeatable runbooks.
• Implement proactive detection, alert correlation, automated diagnostics, and auto-remediation using metrics/logs/traces to reduce MTTR and prevent incidents before user impact.
• Build a domain-aware knowledge graph unifying code, tests, services, incidents, and operational signals; enable RAG-based assistance for PR review, security checks, onboarding, and support triage.
• Define governance, safety, security, and explainability patterns for agentic systems on BTP and hyperscalers; ensure compliance, auditability, and human-in-the-loop controls.
• Set platform and developer experience standards for AI-assisted development, CI/CD, and environment management that scale across SAP Procurement Engineering.
• Translate platform capabilities into measurable outcomes—faster feedback cycles, lower MTTR, cost savings, higher release confidence, and accelerated feature delivery.
• Handle enterprise-scale agentic AI, intelligent CI/CD, Kubernetes operators, knowledge graphs, and domain-aware automation.
• Own portfolio-wide engineering productivity and DevEx strategy; provide end-to-end ownership from architecture to measurable business outcomes.
• Uplift organizational capabilities in AI/ML, platform thinking, SRE/DevOps, and modern testing practices across multiple engineering groups.
• Partner with product, SRE, Security, and platform organizations; influence company-wide technical strategy and work directly with senior leadership.
• Define reference architectures and standards for AI-native productivity platforms, Kubernetes-native orchestration, and intelligent testing; contribute patterns back to SAP\'s enterprise architecture.
• Demonstrate experience with AI-enabled platforms, cloud-native systems, CI/CD, and developer experience; 10–15+ years overall with 7–10+ years in platform/architecture leadership.

Role Requirements

• Strategic Technology Leadership
• Polyglot Engineering: Java/JVM (Spring), plus Go and/or Python and TypeScript/Node for platform, tooling, and operator development.
• Technology Strategy: Tracking and adopting emerging technologies (LLMs, multi-agent RL, vector search, graph databases) and translating them into scalable, secure enterprise platforms.
• Enterprise Integration Mastery
• Data Architecture: Graph databases, vector stores; data governance, lineage, and access controls
• APIs and Protocols: REST, GraphQL, gRPC; OAuth2/OIDC; familiarity with OData and enterprise integration patterns
• Eventing and Messaging: Kafka or equivalent streams; real-time processing and CQRS; WebSockets for collaborative experiences
• Platform Architecture
• Cloud-Native at Scale: Kubernetes (EKS/GKE/AKS), service mesh, multi-tenant SaaS, global resiliency and performance
• Kubernetes Operators: CRD design, reconciliation loops, intelligent scheduling, cluster autoscaling, cost-aware resource management
• Developer Platforms: Internal developer platform design (e.g., Backstage), API management, golden paths, secure toolchains on BTP and major clouds
• AI and Modern Practices
• Production LLM/Agent Systems: Retrieval-augmented generation, tool-use/Function Calling, prompt/retrieval engineering, evaluation, safety, observability
• Reinforcement Learning: Multi-agent RL for classification/decision problems and continuous improvement loops
• MLOps/LLMOps: Model hosting/gateways, feature stores, vector indexes, policy enforcement, red-teaming, telemetry for AI quality
• DevOps Excellence: Trunk-based development, GitOps, progressive delivery, automated experimentation, and performance/scalability testing
• CI/CD and Test Intelligence
• Change-Impact Analysis: Static code analysis, dependency graphs, and historical signal mining
• Pipeline Tooling: Jenkins, GitHub Actions, GitLab CI, Tekton/Argo; caching, parallelization, flaky-test mitigation
• Metrics and Outcomes: Demonstrated reductions of multi-hour pipelines to sub-30 minutes with maintained or improved coverage
• Observability, SRE, and Incident Automation
• Full-Stack Telemetry: OpenTelemetry, Prometheus, Grafana, ELK/Splunk; SLOs, error budgets, auto-diagnostics
• Automated Remediation: Alert deduplication/correlation, runbooks-as-code, safe remediation workflows
• Security, Compliance, and Responsible AI
• Data Security: Secrets management, least-privilege design, governance in regulated contexts
• Responsible AI: Bias testing, explainability, audit trails, human-in-the-loop, policy-compliant agent behavior
• Industry Influence: Ability to influence technology adoption across a large organization

Bring out your best. SAP innovations help more than four hundred thousand customers worldwide work together more efficiently and use business insight more effectively.