Jobs at Elastic

Lead and grow Elastic's UKI Mid‑Market sales organization: set strategy, coach AEs, drive quota attainment, design scalable sales processes, collaborate cross‑functionally, and travel regularly to support deal creation and team needs.

Own full sales cycle for Elastic in the education public sector: drive new logo acquisition and expansion, demonstrate value of Elastic search/observability/security, qualify with MEDDPICC, build strategic territory plans, and partner cross-functionally to close complex deals.

Principal Software Engineer responsible for designing, building, and operating distributed systems powering Serverless Elasticsearch. The role focuses on cluster coordination, concurrent and consistent indexing, scalability, resilience, performance, and operational stability across large-scale deployments. Responsibilities include resolving complex concurrency and performance issues, supporting engineering teams, leading projects across multiple engineers, and owning technical initiatives from design through delivery.

Develop core infrastructure and horizontally scalable APIs for Elasticsearch. Solve complex performance, concurrency, stability, and observability issues; improve developer productivity through automation and AI-enabled workflows; support cloud and serverless operations; and lead cross-team engineering projects from design through delivery.

Leads Elastic’s UK Defence, Intelligence, and National Security sales organization. Responsibilities include managing account executives, developing public-sector sales strategies, leading strategic government deals, designing capture plans and territory models, navigating UK procurement frameworks, driving quota attainment, and collaborating with product, marketing, and partner teams. The role requires regular UK travel, secure-facility engagement, and leadership across complex enterprise SaaS sales cycles.

Leads a distributed team of approximately 12 engineers building Elastic’s conversational and agentic platform. Owns roadmap delivery, hiring, onboarding, coaching, performance management, team processes, and stakeholder communication. Partners with product, technical leadership, data science, UX, and related teams to deliver reliable software involving retrieval, citations, streaming, memory, evaluation, and LLM-powered agents. Requires strong software engineering management experience, technical depth across TypeScript/Node/React and Elasticsearch, and familiarity with RAG, agents, tool use, and evaluation.

Own the production improvement loop for an AI Context Engine, improving agent behavior, retrieval, memory, telemetry, evaluation, and safe rollout. Build production services in TypeScript or Python, design observability and evaluation systems, analyze agent traces and customer feedback, and partner with data scientists, backend engineers, product, and UX. Mentor engineers, review designs, and shape the technical roadmap for agentic products with public APIs and evolving data models.

Own the strategy and roadmap for Elastic’s Streams telemetry pipeline, including data collection, ingestion, processing, routing, and integrations. Lead a distributed product management team, define adoption KPIs, collaborate across Observability, Security, and Search, and improve self-service data ingestion. Partner with customers, engineers, designers, sales, marketing, and the community to prioritize and deliver platform capabilities, messaging, and measurable product outcomes.

Lead competitive benchmarking for Elasticsearch across search, vector retrieval, analytical, and observability workloads. Build automated benchmark harnesses, datasets, query sets, and reproducible test environments; design fair system comparisons; analyze latency, throughput, resource use, cost, and retrieval quality; investigate performance differences; and collaborate with engineering and product teams to drive improvements. Publish clear technical reports and reproducible benchmark artifacts.

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

Lead the vision, strategy, roadmap, and execution for Elastic Agent Builder, a context layer for AI agents. Partner with enterprise customers, sales, solution architects, engineering, data science, design, hyperscalers, and developers to define context engineering capabilities, agent benchmarking, evaluation strategies, and user experiences. Analyze the AI agent market, prioritize customer needs, evangelize the product through content and open-source projects, and drive adoption across a global ecosystem.

Develop and lead full-stack user interface work for Elastic Fleet and Streams using TypeScript, React, and Node.js. Own complex projects end to end, make architecture and system-design decisions, establish coding standards, conduct code reviews, improve testing and deployment, and collaborate asynchronously with designers, product managers, and distributed engineering teams. Build scalable interfaces for observability, log ingestion, and real-time data workflows while mentoring teammates and promoting secure, maintainable software.

Owns the technical vision and roadmap for organization-wide CI/CD and release infrastructure. Identifies and remediates performance bottlenecks and supply-chain security risks, designs scalable release gates, directs engineers through complex multi-quarter projects, and leads incident response. The role requires hands-on debugging across the pipeline stack, cross-organizational influence, technical communication, mentorship, code and design reviews, and setting engineering standards.

Develop and maintain Elasticsearch’s Inference API and plugin framework, integrating internal and external AI providers. Responsibilities include API and protocol design, streaming, asynchronous execution, rate limiting, configuration, billing integration, error handling, open-source contribution reviews, incident response, and comprehensive unit, REST, and rolling-upgrade testing. The role requires advanced Java expertise, concurrency and parallelism knowledge, API design skills, cross-functional collaboration, and autonomous work in a distributed team.

Lead the technical vision and development of Elasticsearch’s core search infrastructure, including indexing, retrieval, query execution, and relevance. Research search algorithms and data structures, contribute to Lucene, guide technical roadmaps, collaborate across teams, mentor senior engineers, and build high-performance distributed search systems. Serve as a subject-matter expert while driving projects from concept through completion.

Design and deploy enterprise search solutions using generative AI, RAG, ELSER, semantic search, vector search, and vector databases. Lead proof-of-concept projects, demonstrate search and retrieval capabilities, evangelize Elastic’s AI-powered search vision through presentations and content, and collaborate with engineers, data scientists, and industry experts. Continuously evaluate emerging AI and search technologies while sharing knowledge across the Solutions Architecture organization.

Build and evolve Elastic’s MCP server, agent skills platform, developer tooling, CLI enhancements, and third-party AI ecosystem integrations. Develop and support libraries and integrations primarily in Go, with Rust and other languages. Establish evaluation-based correctness standards, collaborate with product teams and external partners, contribute product thinking, and improve developer experience across a globally distributed team.

Serves as a technical authority and trusted advisor during sales cycles, translating customer goals into Elastic-based architectures and value propositions. Responsibilities include technical discovery, demonstrations, solution positioning, partner enablement, customer relationship development, event participation, sales collateral creation, and communicating customer needs to engineering and leadership. The role requires technical presales expertise, knowledge of AI enterprise search, observability, or cybersecurity, strong communication and influencing skills, and 30% regional travel.

Own the full sales cycle for mid-market accounts, driving adoption and expansion of Elastic’s search, AI, observability, and security solutions. Build territory plans, identify use cases, conduct discovery, manage complex sales cycles, negotiate contracts, and close deals. Partner with Solutions Architects, Customer Success, Marketing, and RevOps while forecasting accurately and positioning technical capabilities against measurable business outcomes.

Build and grow strategic GSI and Influence Partner relationships across the UK Public Sector. Enable partner-sourced pipeline, lead joint GTM initiatives, develop partner capabilities, and drive co-sell/co-delivery motions across security, observability, search, and AI to deliver measurable customer outcomes and revenue growth.