Note: The job is a remote job and is open to candidates in USA. Elastic is a search AI company whose cloud-based platform provides search, security, observability, and AI capabilities. The Principal Software Engineer will lead strategic build-versus-buy initiatives within Information Technology, designing and delivering Elastic-native internal platforms and systems. The role establishes engineering standards, collaborates across IT, Security, Platform Engineering, and Finance, and validates Elastic products through internal use.
Responsibilities
- 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
- 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 as the data and intelligence layer
- As a Principal Engineer, you will establish and own the architectural standards, design patterns, and engineering practices for all IT platform engineering work. You will define how internal systems are built — data models, API design, observability, cost governance, security posture — and be the technical authority others look to when decisions get hard
- You will partner closely with Elastic's IT infrastructure team, the Security organization (Elastic Security is your SIEM backbone), the Platform Engineering team, and Finance. You will engage with tool owners across the company to understand requirements, challenge assumptions about what needs to be bought versus built and ensure that the systems you build actually get used
- A significant part of the role is running Elastic's own technology in the most demanding possible context: as the engineer responsible for the internal systems that the company depends on every day. Every system you build is a reference architecture. Every insight you generate about what works and what doesn't feed directly into Elastic's product and go-to-market strategy
Skills
- 15+ years of software engineering experience, with at least 3 years as a principal engineer
- Deep, hands-on expertise with Elasticsearch — data modelling, query design, aggregations, performance tuning, and production operations. This is not a role for someone who has read the documentation; we need someone who has run Elasticsearch at scale and can debug it in production
- Strong full-stack engineering capability: you can build and own a system end-to-end, from Logstash ingest pipelines to Kibana dashboards to a React frontend, without needing to hand off each layer to a different team
- Proven track record of building and shipping commercial software or platform systems — not just maintaining existing ones. We want to see examples of systems you originated and delivered
- Architectural judgment: the ability to scope a problem correctly, choose the right components, and make the call on when to build versus integrate versus buy. You have opinions about this, and you can defend them with data
- Strong written communication. You will write architecture decision records, engineering standards documents, and build-vs-buy analyses. Your writing needs to be clear and persuasive to both engineering and non-engineering audiences
- Prior experience building on the Elastic Stack beyond basic logging — Elastic ML, ELSER semantic search, vector search, Kibana Canvas, Watcher, or Elastic Security
- Experience with FinOps practices: cloud cost management, LLM API cost attribution, or building cost visibility tooling
- Familiarity with Information Technology managed systems — not necessarily Salesforce or ServiceNow expertise, but an understanding of the domain problems these tools solve
- Experience working in a hypergrowth or post-IPO technology company where engineering rigor and business speed have to coexist
- Experience with LLM integration patterns: RAG pipelines, prompt engineering for enterprise use cases, LLM gateway design, or AI-powered workflow automation
- Contributions to internal developer experience, platform engineering, or engineering productivity tooling
Benefits
- This role is currently eligible to participate in Elastic's stock program.
- Our total rewards package also includes a company-matched 401k with dollar-for-dollar matching up to 6% of eligible earnings.
- Health coverage for you and your family in many locations
- Ability to craft your calendar with flexible locations and schedules for many roles
- Generous number of vacation days each year
- We match up to $2000 (or local currency equivalent) for financial donations and service
- Up to 40 hours each year to use toward volunteer projects you love
- Embracing parenthood with minimum of 16 weeks of parental leave
Company Overview
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