Datadog
Senior Applied Scientist - Observability Data Platform
Datadog, Boston, Massachusetts, us, 02298
Overview
Senior Applied Scientist - Observability Data Platform The Observability Data Platform (ODP) powers the core of Datadog’s telemetry systems, handling exabytes of multimodal observability data. As AI agents become first-class consumers of telemetry, ODP is evolving to meet their demands — scaling with explosive data growth, exposing new query mechanisms, rethinking how telemetry is stored, transformed, and served, and enforcing guardrails that ensure security and reliability. Our team is building an intelligent control plane for production systems, moving beyond passive monitoring to enable AI agents to safely and effectively take action in live environments. This involves integrating techniques from symbolic reasoning, formal methods, and generative AI. We are looking for an experienced Senior Applied Scientist with a background spanning systems engineering, AI, and formal reasoning. You have expertise in causal modeling, generative simulation, runtime verification, or reinforcement learning, and are motivated to apply these skills to build reliable systems. You will join the team behind Datadog’s most ambitious projects: evolving observability infrastructure for stochastic, self-improving systems. Datadog values people from all walks of life. We understand not everyone will meet all the above qualifications on day one. If you’re passionate about technology and want to grow your skills, we encourage you to apply. What You’ll Do
Design and prototype intelligent systems for AI-native observability, including cost-aware agent orchestration, adaptive query execution, and self-optimizing system components. Apply reinforcement learning, search, or hybrid approaches to infrastructure-level decision-making, such as autoscaling, scheduling, or load shaping. Collaborate with AI researchers and platform engineers to design experimentation loops and verifiers that guide LLM outputs using runtime metrics and formal models. Explore emerging paradigms like AI compilers, “programming after code,” and runtime-aware prompt engineering to inform Datadog’s infrastructure and product design. Help define the direction of BitsEvolve — Datadog’s optimization agent that uses LLMs and evolutionary search to discover code improvements, optimize GPU kernels, and tune configurations to improve performance. Partner with product teams and platform stakeholders to ensure scientific advances translate into measurable improvements in cost, performance, and observability depth. Who You Are
You have a BS/MS/PhD in a scientific field or equivalent experience. You have 8+ years of experience in systems engineering, database internals, or infrastructure research, including hands-on experience in a production environment. You have a strong software engineering foundation, ideally in C++, Rust, Go, or Python, and are comfortable writing performant, maintainable code. You have deep expertise in at least one of the following areas: query optimization, data center scheduling, compiler design, reinforcement learning, or distributed systems design. You have experience applying search, planning, or learning techniques to solve real-world optimization problems. You are excited by systems that learn, adapt, and improve over time using feedback from runtime metrics and human-defined objectives. You are hypothesis-driven and enjoy designing experiments and evaluation loops, whether through simulations, benchmarks, or live systems. You thrive in ambiguity, enjoy reading papers and building prototypes, and want to help shape the future of infrastructure in the AI era. You enjoy collaborating across research, engineering, and product to bring scientific insights to practical outcomes. Benefits and Growth
Get to build tools for software engineers, just like yourself, and use the tools we build to accelerate development. Have a lot of influence on product direction and impact on the business. Work with skilled, knowledgeable, and kind teammates who are happy to teach and learn. Competitive global benefits. Continuous professional development. Equal Opportunity
Datadog is proud to offer equal employment opportunity to everyone regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, and other characteristics protected by law. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. Here are our Candidate Legal Notices for your reference. Privacy and AI Guidelines: Any information you submit to Datadog as part of your application will be processed in accordance with Datadog’s Applicant and Candidate Privacy Notice. For information on our AI policy, please visit Interviewing at Datadog AI Guidelines.
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Senior Applied Scientist - Observability Data Platform The Observability Data Platform (ODP) powers the core of Datadog’s telemetry systems, handling exabytes of multimodal observability data. As AI agents become first-class consumers of telemetry, ODP is evolving to meet their demands — scaling with explosive data growth, exposing new query mechanisms, rethinking how telemetry is stored, transformed, and served, and enforcing guardrails that ensure security and reliability. Our team is building an intelligent control plane for production systems, moving beyond passive monitoring to enable AI agents to safely and effectively take action in live environments. This involves integrating techniques from symbolic reasoning, formal methods, and generative AI. We are looking for an experienced Senior Applied Scientist with a background spanning systems engineering, AI, and formal reasoning. You have expertise in causal modeling, generative simulation, runtime verification, or reinforcement learning, and are motivated to apply these skills to build reliable systems. You will join the team behind Datadog’s most ambitious projects: evolving observability infrastructure for stochastic, self-improving systems. Datadog values people from all walks of life. We understand not everyone will meet all the above qualifications on day one. If you’re passionate about technology and want to grow your skills, we encourage you to apply. What You’ll Do
Design and prototype intelligent systems for AI-native observability, including cost-aware agent orchestration, adaptive query execution, and self-optimizing system components. Apply reinforcement learning, search, or hybrid approaches to infrastructure-level decision-making, such as autoscaling, scheduling, or load shaping. Collaborate with AI researchers and platform engineers to design experimentation loops and verifiers that guide LLM outputs using runtime metrics and formal models. Explore emerging paradigms like AI compilers, “programming after code,” and runtime-aware prompt engineering to inform Datadog’s infrastructure and product design. Help define the direction of BitsEvolve — Datadog’s optimization agent that uses LLMs and evolutionary search to discover code improvements, optimize GPU kernels, and tune configurations to improve performance. Partner with product teams and platform stakeholders to ensure scientific advances translate into measurable improvements in cost, performance, and observability depth. Who You Are
You have a BS/MS/PhD in a scientific field or equivalent experience. You have 8+ years of experience in systems engineering, database internals, or infrastructure research, including hands-on experience in a production environment. You have a strong software engineering foundation, ideally in C++, Rust, Go, or Python, and are comfortable writing performant, maintainable code. You have deep expertise in at least one of the following areas: query optimization, data center scheduling, compiler design, reinforcement learning, or distributed systems design. You have experience applying search, planning, or learning techniques to solve real-world optimization problems. You are excited by systems that learn, adapt, and improve over time using feedback from runtime metrics and human-defined objectives. You are hypothesis-driven and enjoy designing experiments and evaluation loops, whether through simulations, benchmarks, or live systems. You thrive in ambiguity, enjoy reading papers and building prototypes, and want to help shape the future of infrastructure in the AI era. You enjoy collaborating across research, engineering, and product to bring scientific insights to practical outcomes. Benefits and Growth
Get to build tools for software engineers, just like yourself, and use the tools we build to accelerate development. Have a lot of influence on product direction and impact on the business. Work with skilled, knowledgeable, and kind teammates who are happy to teach and learn. Competitive global benefits. Continuous professional development. Equal Opportunity
Datadog is proud to offer equal employment opportunity to everyone regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, and other characteristics protected by law. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. Here are our Candidate Legal Notices for your reference. Privacy and AI Guidelines: Any information you submit to Datadog as part of your application will be processed in accordance with Datadog’s Applicant and Candidate Privacy Notice. For information on our AI policy, please visit Interviewing at Datadog AI Guidelines.
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