Principal, Agentic Engineering Platform

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 AI is fundamentally transforming how professional services teams build and deliver value. At Elastic, we are focused on creating production-grade services platforms and software engineering practices that work reliably in real-world environments. The agentic engineering platform is a suite of tools designed to automate complex, multi-step delivery workflows across our global services organization. We are looking for a Principal, Agentic Engineering Platform to lead this initiative end-to-end. In this role, you will design, ship, and refine agentic systems that directly support our services team. You will set technical standards, guide product strategy, and manage the complete life cycle: building, testing, deploying, monitoring, and iterating. While automated agents expand what you can deliver, you are the architect and decision-maker responsible for the final outcome. A key early priority is DIMA, Elastic's migration automation platform for SIEM and observability projects. Experience in security, SIEM, or observability will be highly valuable. What You Will Be Doing • Services Product Engineering & Platform Leadership: • Establish the technical vision and architectural standards for services agentic systems, ensuring automated tools enhance rather than replace engineering judgment. • Manage the platform roadmap and release schedule, overseeing stages from discovery and classification to quality assurance and rollout. • Develop multi-step workflows using LLM orchestration, tool integration, retrieval-augmented generation (RAG), and structured output processing. • Guide AI-assisted development workflows with tools like Claude Code and Codex, emphasizing issue-focused tasks, automated testing, and security reviews. • Design robust system architecture that addresses operational boundaries, potential failure modes, human approval steps, and long-term maintainability. Evaluation, Quality & Observability: • Create and maintain evaluation frameworks to assess agent performance across accuracy, reliability, response time, cost, and stability. • Implement tracing across tool calls, context assembly, and decision logic to troubleshoot and resolve production issues quickly. • Define quality benchmarks for professional services workflows and build system metrics to validate them. • Incorporate human review checkpoints wherever model output affects client deliverables or operational risk. Field Integration & Collaboration: • Ensure platform outputs generate clear evidence suitable for client deliverables, including proposals, statements of work, and project estimates. • Act as the key technical link between services platform engineering and delivery teams, working closely with stakeholders to seamlessly integrate agentic workflows into existing processes. • Partner with Services Practice Leads and the Global Specialist to turn operational strategies into practical tools. What You Bring • 10+ years of experience in platform engineering, software engineering, or technical professional services roles. • Proven track record of deploying agentic or LLM-powered applications to production, with experience navigating the full deployment and optimization life cycle. • Practical experience with LLM orchestration, prompt engineering, tool integration, and RAG architectures. • Experience building evaluation systems, test suites, and monitoring tools for probabilistic models. • Familiarity with developer tooling (such as Claude Code or Codex) and agent framework patterns. • Strong Python engineering skills, with the ability to review backend services and data structures for production readiness. • Focus on security best practices, including access control, least privilege, air-gapped setups, and safe handling of sensitive customer data. • Strong communication skills, capable of explaining technical trade-offs and deployment risks to non-technical stakeholders. • Willingness to travel up to 15% as needed. Bonus Points • Domain experience in SIEM, observability, or data migration (e.g., detections, ECS, Kibana Security, SPL). • Familiarity with Elastic workflows, such as Kibana SIEM migrations, DIMA, or related migration tooling. • Experience using Elasticsearch as a retrieval or search layer within agentic systems. • Understanding of air-gapped environments and public-sector compliance requirements. • Background in developing technical enablement or training programs for engineering teams. • Relevant certifications across AI/ML, cloud platforms, or security technologies. Compensation for this role is in the form of base salary. This role does not have a variable compensation component. The typical starting salary range for new hires in this role is listed below. In select locations (including Seattle WA, Los Angeles CA, the San Francisco Bay Area CA, and the New York City Metro Area), an alternate range may apply as specified below. These ranges represent the lowest to highest salary we reasonably and in good faith believe we would pay for this role at the time of this posting. We may ultimately pay more or less than the posted range, and the ranges may be modified in the future. An employee's position within the salary range will be based on several factors including, but not limited to, relevant education, qualifications, certificat