Principal Software Engineer

Elastic · United States

In short

▸Liderar la construcción de herramientas internas con Elasticsearch y IA en lugar de usar SaaS costosos.
▸Diseñar y desarrollar plataformas internas que unifiquen herramientas, mejoren la eficiencia y usen IA para costos y seguridad.
▸Oportunidad única de ingeniería de producto dentro de IT, usando la plataforma que la empresa vende.

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What they ask for

✓Experiencia comprobada en arquitectura de sistemas a gran escala.
✓Capacidad para evaluar y decidir build-vs-buy en entornos empresariales.
✓Conocimiento profundo de Elasticsearch, Kibana y capacidades de IA de Elastic.
✓Habilidades de liderazgo técnico y toma de decisiones estratégicas.
✓Experiencia en desarrollo de herramientas internas o plataformas de productividad.
✓Capacidad para trabajar con equipos de IT, Finanzas y liderazgo técnico.

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ElasticsearchKibanaElastic MLElastic ObservabilityElastic SecurityLLM GatewayRAG pipelinesAnthropicOpenAI CodexGitHub Copilot

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Elastic, the Search AI Company, enables everyone to find the answers they need in real time, using all their data, at scale — unleashing the potential of businesses and people. The Elastic Search AI Platform, used by more than 50% of the Fortune 500, brings together the precision of search and the intelligence of AI to enable everyone to accelerate the results that matter. By taking advantage of all structured and unstructured data — securing and protecting private information more effectively — Elastic’s complete, cloud-based solutions for search, security, and observability help organizations deliver on the promise of AI. What is The Role The enterprise software landscape is undergoing a structural shift. AI-assisted development has dropped the cost and time required to build custom internal tools by more than half. Retool's 2026 State of Internal Software report found that 35% of enterprises have already replaced SaaS tools with purpose-built software, and 78% plan to build more in the year ahead. The calculus has changed: what previously required a six-figure vendor contract and a year-long implementation is now a small engineering team and a few focused sprints. Elastic is at the beginning of this journey. We operate the Elastic Stack — Elasticsearch, Kibana, Elastic ML, and a growing set of AI-native capabilities — at production scale for thousands of customers. And we are increasingly building on our own platform internally: replacing expensive SaaS tools with Elastic-native systems that are faster, more intelligent, and owned entirely by us. We are looking for a Principal Engineer to join our Information Technology team to be part of this effort. This is not a support role or a tools administrator position. It is a senior engineering role for someone who can look at a $500,000 annual SaaS contract and ask: 'Could we build a better version of this on Elasticsearch in twelve weeks?' — and then go do it. This is a rare opportunity to do original product engineering inside an IT organization, working with a platform that most engineers only get to use as a customer — and to build systems that directly shape how a public company operates. What You Will Be Doing Lead strategic build-vs-buy Engineering You will work with IT leadership, Finance, and Engineering to evaluate Elastic's internal SaaS portfolio and identify where custom-built systems — backed by Elasticsearch, Kibana, and Elastic's AI capabilities — deliver better value than continued vendor contracts. You will own the architecture, engineering systems, build plan, and delivery of the highest-priority replacements. Design and build Elastic-native internal platforms The project portfolio spans four areas where the build-vs-buy shift is most compelling: • Platform productivity tools — internal developer portals, knowledge search layers, engineering onboarding systems, and workspace tooling that unifies disparate SaaS tools into a single Elasticsearch-backed search and intelligence layer. • FinOps and AI cost governance — a consolidated cost visibility and anomaly detection system across Elastic's AI providers (Anthropic, OpenAI Codex, GitHub Copilot, Google Gemini) and cloud platforms (AWS, GCP, Azure), replacing commercial FinOps SaaS with an Elastic ML-powered alternative. • IT service management — evaluating and building replacements for commercially purchased SaaS products including incident management, knowledge base search, internal developer portal, and SIEM-correlated security workflows, using Elastic Observability and Elastic Security as the backbone. • Enterprise efficiency systems — custom tooling that reduces manual process overhead across IT, Finance, HR, and Operations, using the LLM Gateway, RAG pipelines, and Elasticsearch

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