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Develops Elastic’s footprint within UK Defence by expanding existing business, building relationships, generating demand, identifying use cases, managing complex sales cycles, closing transactions, and growing territory revenue through customer, partner, and defence community ecosystems. The role requires SaaS sales expertise, defence-sector relationships, accurate forecasting, open-source go-to-market knowledge, and an active security clearance.

Leads procurement analytics, spend reporting, contract reviews, RFPs, vendor negotiations, and tail-spend management. Analyzes procurement data, develops metrics and recommendations, supports sourcing optimization, maintains procurement systems, administers configurations, and helps implement new tools. The role collaborates with Legal, Finance, IT, sourcing teams, and suppliers, while providing training and supporting process and change management initiatives.

Lead Elastic’s strategy, vision, and multi-quarter roadmap for vector databases, embedding and reranking models, vector indexing, semantic ingestion, and search capabilities. Conduct market and competitive research, define product metrics, prioritize features, and partner closely with engineering, cloud, and applied research teams. Guide technical trade-offs involving recall, latency, index size, ingestion throughput, model lifecycle, and total cost of ownership across serverless and self-managed deployments.

Lead the technical vision and development of Elasticsearch’s core search infrastructure, including indexing, retrieval, query execution, and relevance. Research advances in search systems and algorithms, guide long-term technical roadmaps, collaborate across teams, mentor expert engineers, and contribute hands-on to high-performance distributed software. Serve as a subject-matter authority while driving projects from concept through completion.

Provide EMEA Deal Desk support partnering with Sales, Finance, and Legal to structure, approve, and optimize complex SaaS deals. Manage non-standard approvals, enforce revenue recognition and compliance, maintain legal template repository, build CRM workflows, support quoting-to-cash processes, and drive process and system improvements to scale global Deal Desk operations.

Lead and grow Elastic's Justice & Public Safety business across the UK. Build executive relationships across government and blue light organizations, drive strategic pursuits, expand Elastic's platform (Search, Security, Observability, AI), and collaborate with cross-functional teams. Mentor colleagues, develop partner ecosystems, and deliver sustainable pipeline, customer outcomes, and platform revenue growth while preparing to scale the business.

Develop and optimize Elasticsearch performance across distributed and serverless architectures. Build performance models, profiling and benchmarking workflows, regression detection, and AI-assisted optimization harnesses. Analyze bottlenecks in logging, metrics, vector search, and ES|QL; implement scalable, thread-safe, high-performance Java code; and collaborate across teams through technical reviews and guidance. Experience with JVM internals, distributed systems, performance engineering, and benchmarking is required.

Leads architectural and code-level performance engineering for Elasticsearch, from design through production. Develops performance models, profiles distributed systems, identifies bottlenecks, builds benchmarks and regression detection, and drives optimization across logging, metrics, vector search, and ES|QL. Designs AI-assisted optimization harnesses, collaborates across teams, and mentors engineers while improving scalability, predictability, and performance.

Lead architectural and code-level performance engineering for Elasticsearch, from design through production. Develop performance models, profile distributed systems, identify bottlenecks, optimize stateful and serverless architectures, and build benchmarking and regression-detection automation. Drive AI-assisted optimization tooling, collaborate across teams, and mentor engineers. Focus areas include Java and JVM performance, concurrency, distributed systems, logging, metrics, vector search, ES|QL, storage engines, and scalable search infrastructure.

Lead Elasticsearch performance engineering from architecture through production. Develop performance models, optimize distributed systems, profile bottlenecks, build benchmarks, detect regressions, and improve scalability across stateful and serverless architectures. Design AI-assisted optimization and benchmarking tools, collaborate across teams, define performance strategies, and mentor engineers. The role requires deep Java, JVM, concurrency, distributed systems, and search or data-store performance expertise.