Senior Product Solutions Architect - LLM Observability

<p>The Product Solutions Architecture (PSA) team acts as a technical multiplier across Datadog. PSAs are domain experts who partner with Field teams on complex customer use cases across pre- and post-sales engagements and scale their impact by producing reusable collateral, including reference architectures, technical guides, and enablement assets. By feeding real-world customer insights back to Datadog Product teams, PSAs help influence product roadmaps while accelerating adoption, usage, and long-term customer success.</p> <p>Datadog’s LLM Observability product enables organizations to monitor, troubleshoot, and optimize large-scale LLM-powered applications with confidence, while meeting requirements around data privacy, compliance, and cost management. As a Product Solutions Architect, you will partner closely with Datadog customers and the LLM Observability product team to design architectures, implement best practices, and drive adoption of LLM observability across customer environments.</p> <p><em>At Datadog, we place value in our office culture - the relationships and collaboration it builds, and the creativity it brings to the table. We operate as a hybrid workplace to ensure our Datadogs can create a work-life harmony that best fits them.</em></p> <p>What You’ll Do:</p> <ul> <li>Serve as the in-house subject matter expert for Datadog’s LLM Observability product</li> <li>Partner with Field teams to provide hands-on technical and architectural guidance to enterprise customers adopting LLM Observability</li> <li>Create high-impact technical collateral, including reference architectures, technical guides, cookbooks, and documentation to enable Field teams and the broader customer community</li> <li>Build proofs of concept and small-scale deployments to validate solutions and reproduce real-world customer environments</li> <li>Act as a trusted advisor to Product Management by delivering actionable feedback informed by real-world field experience</li> </ul> <p>Who You Are:&nbsp;</p> <ul> <li>You bring a strong software engineering foundation, with hands-on experience building and operating LLM-powered applications in production environments at a large scale, and are comfortable diving deep into codebases to understand architectural decisions, tradeoffs, and implementation details</li> <li>You are familiar with distributed systems and core observability concepts, such as tracing, metrics, and logging, and can translate those patterns into the emerging LLM observability domain, including LLM spans, evaluations, and prompt templates</li> <li>Experience with languages such as Python and/or JavaScript/TypeScript</li> <li>Comfortable operating in rapidly evolving, ambiguous technical domains</li> <li>You build deep context across teams and trans