Join the Elasticsearch Search Relevance team to design and implement search features (including vector search using HNSW/IVF), improve Lucene integration, write modern Java, triage and handle community issues, and collaborate with a globally distributed engineering team on open source development.

Join the globally distributed Elasticsearch Search Relevance team to design and implement new search features, improve relevance (including contributions to Lucene), work on vector search algorithms (HNSW, IVF), and build high-performance Java code. The role involves collaborating with community members and distributed engineers, debugging complex systems, and contributing to open source.

Elastic is hiring a Senior Software Engineer for the Elasticsearch - Search Relevance team to lead initiatives that improve search speed and relevance, contribute new search features and fixes (including work touching Lucene), and collaborate with a globally distributed engineering team. The role emphasizes expertise in search/vector databases and algorithms (e.g., HNSW, IVF), strong core Java skills, open-source collaboration, and autonomous, asynchronous distributed-team working.

Join the globally distributed Elasticsearch Search Relevance team to lead development of search features, improve Lucene, and work on vector search capabilities. Responsibilities include designing and implementing algorithms and data structures, fixing complex bugs, collaborating across a distributed team, and writing idiomatic modern Java. Required experience includes search or vector databases and familiarity with algorithms such as HNSW or IVF; experience with data storage technologies (Elasticsearch, Solr, PostgreSQL, MongoDB, Cassandra) and using AI tools to aid development is highlighted.

Work as a senior engineer on Elasticsearch's Search Relevance team to design and implement search features and algorithms (including vector search and work with HNSW/IVF), contribute to Lucene, fix bugs, and collaborate with a distributed, open-source-focused team. Role emphasizes modern Java development, system-level and algorithmic work, and collaboration across distributed teams. Compensation includes a listed CAD annual salary range, benefits, and participation in stock program.

Serve as the commercial technical contact for enterprise accounts, demonstrate and architect Elastic Stack solutions, enable sales and partners, engage community events, and act as voice of the customer. Requires minimum 4 years in technical presales and willingness to travel ~20%.

Elastic is hiring an Inside Account Executive for the Japanese territory to build pipeline, run outbound cadences, perform deep discovery and qualification (using frameworks like MEDDPICC), deliver tailored demos and value storytelling, and negotiate multi-year consumption commitments. The role requires proven SaaS quota-carrying success (3+ years), fluency in Japanese and English, strong negotiation skills, and collaboration with Solutions Architects, Customer Success, Marketing, and RevOps.

Elastic is hiring a Senior Security Research Engineer to research attacker techniques, build endpoint visibility and protections, reverse engineer malware, develop high-performance C/C++ production code, and lead technical initiatives. The role requires 6+ years of experience in TTP analysis and detection, development in C/C++/Python, deep OS internals knowledge (Windows prioritized), and malware/reverse-engineering expertise. Compensation is provided as base salary (USD range listed).

Lead ABM strategy, account-level planning, campaign execution, measurement, and event coordination across the Americas. Requires 5–6 years B2B marketing experience (minimum 5 years), including ABM/field marketing experience and familiarity with ABM platforms (e.g., Demandbase, 6sense), Salesforce, and Marketo. Focus areas include cybersecurity, search, AI/ML, and observability.

Responsible for crafting, executing, and measuring account-based marketing (1:1 and 1:few) for Public Sector (PubSec) accounts in AMER. Works cross-functionally with sales, customer success, product marketing, and external agencies to deliver personalized campaigns (paid media, executive briefings, events, content syndication) that address government use cases (cybersecurity, data analytics, AI/ML, observability). Requires 5+ years B2B marketing experience, ABM tools knowledge (Demandbase/6sense/Userled), Salesforce and marketing automation (Marketo), and familiarity with government procurement and compliance (GSA, SEWP, FedRAMP).

Elastic is hiring a Senior Salesforce Engineer to own end-to-end design, development, testing, deployment, and support of Salesforce and integration solutions. The role involves Lightning Web Components, Apex, SOQL/SOSL, Flows, REST APIs, event-driven patterns, CI/CD, and use of AI-assisted coding tools (Cursor, Claude Code, Codex, Copilot). The role expects 5+ years of full-stack engineering experience. Typical starting salary range: $94,300–$149,200 USD per year.

Owner of a defined territory responsible for building pipeline, closing complex multi-stakeholder enterprise deals in a consumption-based model, and collaborating with Solutions Architects and Customer Success. Requires 5+ years of SaaS enterprise quota-carrying experience, strong discovery/qualification (e.g., MEDDPICC), negotiation skills, and technical/cloud fluency across search, observability, and security use cases.

Lead architect role responsible for assessing, designing, implementing and delivering Elastic Observability solutions for enterprise customers. Responsibilities include solution architecture, hands-on deployments (data onboarding, configuration, visualizations, alerting), cluster tuning and scaling, capacity planning, migrations, technical workshops, mentoring, and engagement with Sales, Engineering and Product teams. Minimum 8 years’ experience as a Consulting Architect or senior IT leader and hands‑on experience with Elasticsearch/Lucene, cloud and on‑prem platforms (AWS/Azure/GCP/OpenStack), Linux, containerization, DevOps and scripting (Python, JavaScript, Go, etc.). Based in Australia with occasional travel as required.

Lead role requiring 12+ years of full‑stack engineering experience to design, build, and own end‑to‑end features (UI, APIs, backend, data models) and Salesforce components (LWC, Apex, SOQL). Use AI‑assisted coding tools (Cursor, Claude Code, Codex, Copilot), implement integrations (REST, event‑driven, MuleSoft), contribute to CI/CD and automated testing, and provide production support.

Elastic is hiring a Senior Public Sector Account Executive focused on the UK Defence sector to expand existing business, build new relationships, and close complex transactions. The role requires experience selling SaaS (Enterprise Search, Logging, Security, APM, Cloud), business development within Defence or Defence primes, ability to build stakeholder credibility, apply sales methodologies and provide accurate forecasting. A current active security clearance is listed as a requirement.

Lead the vision and multi-quarter roadmap for Elastic's vector database and vector/search use cases, partnering with engineering and research. Responsibilities include market and competitive research, defining metrics (recall, latency, index size, throughput, TCO), prioritizing features, and advancing Elastic AI and Vector products across serverless and self-managed deployments. Requires 8+ years in product management and working knowledge of vector search fundamentals and generative/model workflows.

Full-time Principal Software Engineer role contributing to Elasticsearch core search infrastructure (indexing, retrieval, relevance). Responsibilities include defining technical vision, researching search/data-structure advances, leading and contributing to core features, collaborating with product and partner teams, mentoring engineers, and working across distributed teams. Requires deep experience with search technologies (Elasticsearch, Lucene, Solr), core Java, data structures, concurrency, and large-scale distributed systems.

Lead performance engineering initiatives for Elasticsearch, owning technical design and execution of optimizations, building performance models and benchmarks (stateful and serverless), profiling and identifying bottlenecks across logging, metrics, vector search and ES|QL, and driving automation including AI-assisted optimization harnesses. Requires deep Java/JVM knowledge, experience profiling and benchmarking distributed systems, and familiarity integrating native libraries and storage/index performance.

Lead and deliver high-impact performance engineering initiatives for Elasticsearch, including architecture and code improvements, profiling and benchmarking (flamegraphs, JMH, Rally), performance modeling, regression detection, and automation (AI-assisted optimization). Requires deep Java/JVM knowledge, experience with distributed systems and performance tuning, and mentoring other engineers.

Lead high-impact performance initiatives across architecture and code, develop performance models and methodologies for distributed systems, profile and benchmark components (logging, metrics, vector search, ES|QL), drive automation and AI-assisted optimization tooling, and mentor engineers to embed performance-first thinking across the company. Requires deep Java/JVM and distributed systems expertise and experience with profiling and benchmarking tools.