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Product Solutions Architect - FinOps

Datadog · Boston, Massachusetts, USA; Denver, Colorado, USA; New York, New York, USA; San Francisco, California, USA

On-siteEnglish

About the role

From the employer’s listing · Datadog · posted 9 October 2026

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.

Datadog's Cloud Cost Management (CCM) suite helps Platform, Application Teams, Operations, FinOps, and Finance teams understand, allocate, and reduce cloud spend by putting cost data next to the observability data that explains it. As a Product Solutions Architect, you will partner closely with Datadog customers and the Cloud Cost Management product team to design product use cases, implement best practices, and drive adoption of CCM across customer environments. This includes infrastructure cost allocation, cloud costs, token usage, container costs, budgets, and optimization recommendations.

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.

What You'll Do

  • Serve as the in-house subject matter expert for Datadog's Cloud Cost Management products, including cost visibility across AWS, Azure, and GCP, Kubernetes and container cost allocation, custom and SaaS cost ingestion, budgets, anomaly detection, and cost optimization recommendations
  • Provide architectural guidance on capacity planning, comparing cloud service cost models, and balancing performance vs. cost trade-offs across different cloud environments
  • Guide customers on tokenomics and AI cost attribution across providers (Anthropic, OpenAI, AWS Bedrock, Google Gemini, Vertex AI, and GitHub Copilot), helping teams map API keys, models, and usage to teams and business units using Tag Pipelines.
  • Help enterprise clients track real-time AI spend changes, set up cost anomaly monitoring, and connect token usage back to business outcomes and unit economics (such as cost per user or cost per ticket).
  • Partner with Field teams to provide hands-on technical and architectural guidance to enterprise customers adopting CCM, including designing tagging and cost allocation strategies, showback and chargeback models, and cost reporting that connects spend to services, teams, and business units
  • Create high-impact technical collateral, including reference architectures, technical guides, blog articles, and documentation to enable Field teams and the broader customer community, covering topics like cloud billing data onboarding (AWS, Azure, GCP billing), Kubernetes cost attribution, tok

Skills mentioned

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