We're eager to welcome an outstanding Product Manager to join the Elastic Observability product team, with a focus on APM, Synthetics and RUM capabilities. With your knowledge and understanding of the Observability domain, you'll help ensure that we give our customers the best end to end full stack Observability experience for the applications we monitor.
\nThis role significantly impacts the success of our Observability product!
\nResponsibilities
\nWhat You Bring
\nAdditional Information
\nAs a distributed company, diversity drives our identity. Whether you’re looking to launch a new career or grow an existing one, Elastic is the type of company where you can balance great work with great life. Your age is only a number. It doesn’t matter if you’re just out of college or your children are; we need you for what you can do.
\nWe strive to have parity of benefits across regions and while regulations differ from place to place, we believe taking care of our people is the right thing to do.
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\nYou will translate business and technical requirements into scalable, outcome-driven solutions built on the Elastic Stack. You will lead end-to-end delivery of customer engagements , from discovery and design through implementation, enablement, and optimisation. You will partner with customers to architect, deploy, and operationalise Elastic solutions that drive measurable value and adoption.
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\nYou will have proven experience deploying Elastic Observability (APM, UEM, logs, metrics, infra, network monitoring) or similar solutions at enterprise scale. You will have hands-on expertise in distributed systems and large-scale infrastructure. You will have ability to design and build dashboards, visualisations, and alerting thresholds that drive actionable insights.
\nYou will have experience with Kubernetes, Linux, Java, databases, Docker, AWS/Azure/GCP, VMs, Lucene. You will have strong communication and presentation skills, with experience engaging directly with customers. You will have a Bachelor’s, Master’s, or PhD in Computer Science, Engineering, or related field, or equivalent experience.
\nYou will be comfortable working in highly distributed teams, both remote and on-site when needed. You may require significant travel to customer sites to support engagements and solution implementations; candidates should be comfortable with varying levels of travel based on business needs.
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\nKey responsibilities include:
\nRequired skills include:
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\nWrite high-quality, testable backend code in Python or Go/Node.js to power AI-integrated features.
\nInstrument AI components with structured logging, distributed tracing, latency dashboards, and alerting to ensure operational visibility.
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\nDevelop and operate AI features within Jeeves's core financial products: spend categorization, document extraction, anomaly detection, financial Q&A, and automated reconciliation.
\nImplement structured output validation, fallback handling, and confidence scoring to ensure AI decisions meet reliability standards for financial use cases.
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\nEstablish prompt versioning and evaluation practices to ensure AI outputs remain accurate and consistent as models and data evolve.
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\nBuild document ingestion and chunking pipelines for Jeeves's financial data , processing invoices, receipts, policy documents, and transaction records.
\nOptimize retrieval quality through embedding model selection, chunk strategy, metadata filtering, and re-ranking techniques.
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\nBuild and maintain model serving endpoints with appropriate latency SLOs, input validation, and output monitoring.
\nImplement model performance monitoring and data drift detection to ensure production models remain accurate over time.
\nSupport model retraining workflows by designing clean data pipelines and feature engineering that can be continuously updated.
\nBackend Integration & Reliability - Integrate AI services cleanly with Jeeves's backend microservices , designing clear API contracts, circuit breakers, and graceful degradation patterns.
\nWrite high-quality, testable backend code in Python or Go/Node.js to power AI-integrated features.
\nInstrument AI components with structured logging, distributed tracing, latency dashboards, and alerting to ensure operational visibility.
\nCollaboration & Growth - Partner with Product, Backend Engineering, and Data Science to define the AI roadmap and translate requirements into reliable systems.
\nContribute to a culture of quality by writing design docs, reviewing peers' AI system designs, and sharing learnings openly.
\nHelp grow the AI engineering practice at Jeeves by establishing patterns, tooling, and best practices that the broader team can build on.
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