Jobs at Elastic

Build and maintain HR data pipelines and dbt models on GCP and BigQuery, integrating systems such as Workday and Greenhouse. Develop self-service dashboards, recruiting reports, data validation, governance, and AI-powered analytics experiences. Translate HR and recruiting data into actionable insights, improve reporting automation, and support stakeholders with decision-ready information while helping establish scalable analytics processes.

Leads the roadmap, architecture, security, and organizational adoption of CI/CD and release infrastructure. Designs scalable release gates, hardens supply chains, directs engineers through complex projects, manages severe incidents, and drives cross-functional technical alignment. The role remains hands-on through code reviews, prototyping, debugging, documentation, mentorship, and design reviews while primarily achieving impact through team leadership.

Owns Elastic Cloud revenue accounting, including ASC 606 contract reviews, revenue recognition, reconciliations, close support, audit coordination, technical accounting memos, UAT, policy evaluation, process improvements, controls, and internal training. Collaborates with Deal Desk, Order Operations, Billing, Collections, FP&A, and IT/Engineering in a distributed technology environment.

Owns the CI/CD and release infrastructure roadmap, technical vision, security gates, artifact provenance, and organizational adoption. Directs engineers through complex, multi-quarter projects, leads incident response for supply-chain and release issues, and raises engineering standards through mentorship and reviews. Remains hands-on with code, prototyping, debugging, and production issues while improving developer productivity, release safety, and infrastructure scalability.

Own the roadmap and technical vision for CI/CD and release infrastructure. Identify and remediate pipeline bottlenecks and supply-chain security risks, design scalable release gates, direct engineers through complex projects, lead incident response, and establish engineering standards through mentorship, reviews, documentation, and technical alignment.

Leads the roadmap, architecture, and adoption of CI/CD and release infrastructure. Identifies pipeline bottlenecks and security risks, designs scalable release gates, and directs engineers through complex cross-organizational projects. Oversees supply-chain and release incidents, drives continuous improvements, mentors engineers, establishes technical standards, and remains hands-on with code reviews, prototypes, debugging, and production issue resolution.

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.

Lead the roadmap and technical vision for CI/CD and release infrastructure. Identify and resolve bottlenecks and security risks, design scalable release gates, direct engineers through complex cross-organizational projects, manage high-severity incidents, and establish engineering standards. Remain hands-on through code reviews, prototyping, debugging, mentorship, and technical communication while primarily delivering impact through team leadership.

Lead the technical vision and roadmap for CI/CD, release, and platform engineering productivity. Identify and resolve infrastructure bottlenecks and supply-chain security risks, establish scalable release gates, direct engineers through complex cross-organizational projects, and serve as incident commander for critical release incidents. The role also involves technical communication, architecture documentation, code and design reviews, mentorship, prototyping, and production debugging.

Support global FP&A through financial reporting, dashboards, forecasting, budgeting, variance analysis, and month-end close. Partner with business leaders on financial insights and ad hoc analysis. Re-engineer finance processes using AI tools, automate reporting, maintain reconciliations across finance systems, improve data quality, and coach teams on new technologies.

Lead the strategy and execution of customer onboarding and Getting Started content for Elastic products. Create cohesive, user-focused journeys that guide customers from initial setup through successful deployment and feature adoption. Partner with Product, Field, and Documentation teams to align content with product roadmaps and customer needs. Use user research, support feedback, analytics, and telemetry to identify friction, improve time-to-value, and support trial-to-paid conversion.

Lead Elastic’s full sales cycle across India’s Defence, Ministry of Home Affairs, space, security, and intelligence accounts. Build executive and government relationships, develop strategic account plans, identify expansion opportunities, manage complex tenders and procurement processes, oversee proofs of concept and negotiations, and close strategic contracts. Maintain pipeline accuracy, forecasts, and revenue performance while partnering with internal teams and strategic partners to position Elastic’s search, observability, security, SIEM, and AI solutions.

Provides technical support for hardware, software, networks, office peripherals, and user technology issues. Diagnoses and resolves incidents, monitors system performance and logs, manages network devices and security protocols, maintains hardware and software inventories, documents configurations and resolutions, supports onboarding, trains users, and coordinates hardware procurement with vendors.

The Enterprise Account Executive will drive demand for Elastic solutions in new Enterprise accounts, manage the sales cycle, and build relationships with customers.

Develop and optimize Elasticsearch performance across distributed and serverless architectures. Build performance models, profiling and benchmarking tools, regression detection systems, and AI-assisted optimization harnesses. Analyze bottlenecks in logging, metrics, vector search, and ES|QL while implementing high-performance, thread-safe Java code. Collaborate across teams, provide technical guidance, and improve scalability and predictability of Elasticsearch.

Develop and optimize Elasticsearch performance across distributed and serverless architectures. Build performance models, benchmarks, profiling tools, and regression detection for logging, metrics, vector search, and ES|QL. Analyze bottlenecks, implement Java and JVM-level optimizations, and contribute to AI-assisted benchmarking automation. Collaborate across teams, provide technical guidance, conduct peer reviews, and improve the scalability, predictability, and efficiency of Elasticsearch.

Senior Software Engineer on Elastic’s Elasticsearch Performance team, developing and implementing code- and architecture-level optimizations for distributed search systems. Responsibilities include profiling, benchmarking, regression detection, performance modeling, vector search optimization, and building AI-assisted optimization tools. The role requires deep Java and JVM expertise, concurrency knowledge, distributed systems experience, and collaboration across engineering teams.

Build AI-powered observability capabilities across Kibana interfaces, agentic investigation systems, telemetry detection pipelines, and evaluation infrastructure. Develop user-facing investigation workflows, agent tools, context and signal-generation systems, and offline and online evaluations. Collaborate with UX designers, product managers, and data scientists to improve autonomous root-cause analysis and remediation for SREs.

Build AI-powered observability features across Kibana user interfaces, agentic investigation systems, telemetry detection pipelines, and evaluation infrastructure. Develop tools for autonomous root-cause analysis, shape reasoning context, generate detection signals, assess agent output quality, and collaborate with UX, product, and data science teams.

Build AI-powered observability systems for autonomous SRE investigations. Develop Kibana interfaces for investigation workflows, contribute to multi-agent root-cause analysis, create detection and signal-generation pipelines, and build evaluation infrastructure for agent outputs. Collaborate with UX, product, and data science teams. The role requires TypeScript, React, Node.js, and familiarity with LLM systems, agent orchestration, tool use, retrieval, and context management.