Asks for

The ad says“Technical depth, product domain expertise, and AI systems literacy; knowing how AI solutions work, where they fail, and the scope and impact of those failures. AI brings more complexity into the picture - the technical bar is higher, not lower.”
The ad says“Engineering credibility earned through hands-on experience with technically complex domains — observability, infrastructure, data platforms, or AI/ML systems including model training pipelines, ML infrastructure, and GPU compute. You can go deep on architecture and system design, push back on technical decisions, and hold your own in the room with staff engineers and senior ICs.”
The ad says“Engineering credibility earned through hands-on experience with technically complex domains — observability, infrastructure, data platforms, or AI/ML systems including model training pipelines, ML infrastructure, and GPU compute. You can go deep on architecture and system design, push back on technical decisions, and hold your own in the room with staff engineers and senior ICs.”
The ad says“You have managed programs with real unit economics implications - cloud cost, capacity, margin”
The ad says“You have managed programs with real unit economics implications - cloud cost, capacity, margin”
The ad says“Engineering credibility earned through hands-on experience with technically complex domains — observability, infrastructure, data platforms, or AI/ML systems including model training pipelines, ML infrastructure, and GPU compute. You can go deep on architecture and system design, push back on technical decisions, and hold your own in the room with staff engineers and senior ICs.”
The ad says“Engineering credibility earned through hands-on experience with technically complex domains — observability, infrastructure, data platforms, or AI/ML systems including model training pipelines, ML infrastructure, and GPU compute. You can go deep on architecture and system design, push back on technical decisions, and hold your own in the room with staff engineers and senior ICs.”
The ad says“Engineering credibility earned through hands-on experience with technically complex domains — observability, infrastructure, data platforms, or AI/ML systems including model training pipelines, ML infrastructure, and GPU compute. You can go deep on architecture and system design, push back on technical decisions, and hold your own in the room with staff engineers and senior ICs.”
The ad says“You have managed programs with real unit economics implications - cloud cost, capacity, margin”
The ad says“Engineering credibility earned through hands-on experience with technically complex domains — observability, infrastructure, data platforms, or AI/ML systems including model training pipelines, ML infrastructure, and GPU compute. You can go deep on architecture and system design, push back on technical decisions, and hold your own in the room with staff engineers and senior ICs.”
The ad says“Engineering credibility earned through hands-on experience with technically complex domains — observability, infrastructure, data platforms, or AI/ML systems including model training pipelines, ML infrastructure, and GPU compute. You can go deep on architecture and system design, push back on technical decisions, and hold your own in the room with staff engineers and senior ICs.”
The ad says“Engineering credibility earned through hands-on experience with technically complex domains — observability, infrastructure, data platforms, or AI/ML systems including model training pipelines, ML infrastructure, and GPU compute. You can go deep on architecture and system design, push back on technical decisions, and hold your own in the room with staff engineers and senior ICs.”
The ad says“Engineering credibility earned through hands-on experience with technically complex domains — observability, infrastructure, data platforms, or AI/ML systems including model training pipelines, ML infrastructure, and GPU compute. You can go deep on architecture and system design, push back on technical decisions, and hold your own in the room with staff engineers and senior ICs.”
The ad says“3+ years of technical program management at a high-growth technology company”
The ad says“Strong written and verbal communication; comfortable owning the narrative at VP+ levels”
The ad says“Strong written and verbal communication; comfortable owning the narrative at VP+ levels”

TPMs at Datadog see the problems hiding between teams, engineer away the work that shouldn’t require humans, and drive the company’s most technically complex and consequential bets to completion.

About the Role
Technical Program Management at Datadog operates at the intersection of engineering depth and organizational reach by driving high priority, cross-functional programs that are too complex and consequential for any single team to own. We partner with engineering on solving deeply technical problems at scale by connecting the people, decisions, and context to move Datadog's most important work forward.

We build the systems and automation that make entire classes of program work self-executing. We are in the architecture conversation early, earning trust through technical judgment. We use AI to surface risks earlier, accelerate program execution plans, and find cross-team patterns that would otherwise stay hidden. The faster teams move, the more essential it is to have someone who can operate across them.

What we expect
These are the expectations we hold for every TPM at Datadog.

Technical depth, product domain expertise, and AI systems literacy; knowing how AI solutions work, where they fail, and the scope and impact of those failures. AI brings more complexity into the picture - the technical bar is higher, not lower.
Build the systems that reduce the need for coordination
Identify what matters before anyone asks, and automate the rest
Engineer program lifecycles end-to-end
See what no single team can see and own the solution
Drive the company's most technically complex and consequential bets through cross-functional agreement, organizational visibility, and influence
Build AI powered automation tools and deploy them at every stage of program execution

What you will do
See Across: Identify What No Single Team Can See

Own large cross-functional programs spanning multiple engineering orgs, product, and business functions
Proactively surface systemic risks, cross-pod dependencies, and organizational friction before they become escalations
Build and maintain SVP-level visibility through tracked KPIs on Datadog’s highest-priority initiatives
Uses technical credibility, trusted relationships, and product domain expertise to bridge the gaps between functions where misalignment is expensive

Engineer Away: Automate What Shouldn’t Require Humans

Identify repeatable program archetypes and engineer the lifecycle end-to-end with AI solutions; the goal is to make the program run itself
Build automation that reduces the need for coordination, eliminating program overhead so engineers and PMs spend time only on work requiring human judgment
Contribute to the TPM toolkit: AI-powered risk synthesis, dependency tracking, stakeholder mapping, and program templates
Drive the shift from manual coordination to self-executing program infrastructure

Drive Completion: Move The Company’s Most Complex Bets Forward

Lead programs across four archetypes: deep technical, large cross-functional, product delivery, and operational
Accelerate alignment by removing friction and overhead, not by adding process.
Hold the judgment call on when to escalate, when to slow down, when a technical decision has organizational implications
Own outcomes, not activities - your value is measured by what ships and what never had the chance to become a problem

What we are looking for
Required

3+ years of technical program management at a high-growth technology company
Demonstrated ability to drive large, ambiguous, cross-functional programs to completion with minimal direction
Engineering credibility earned through hands-on experience with technically complex domains — observability, infrastructure, data platforms, or AI/ML systems including model training pipelines, ML infrastructure, and GPU compute. You can go deep on architecture and system design, push back on technical decisions, and hold your own in the room with staff engineers and senior ICs.
Track record of earning trust with senior engineering and product leadership - not through title, through judgment
Strong written and verbal communication; comfortable owning the narrative at VP+ levels
Active AI practitioner, you use AI tools in your daily work and can demonstrate how they’ve changed your leverage
You have built something, a tool, a template, an automated workflow, that other people use

Strong Signal

You identified a systemic problem no one asked you to find and built the operating system to solve it
You automated a program lifecycle or workflow that previously required manual coordination
You have operated in observability, infrastructure, data platforms, or AI/ML environments and can speak to the technical architecture, not just the program execution
You have managed programs with real unit economics implications - cloud cost, capacity, margin

Datadog Benefits

New hire stock equity (RSUs) and employee stock purchase plan (ESPP)
Continuous professional development, product training, and career pathing
Assigned TPM mentor and engineering buddy program for learning and relationship building
An inclusive company culture, active Community Guilds (Datadog employee resource groups), in-person team summits, local office programming
Competitive global benefits; free, mental health benefits for employees and dependents age 6+

At Datadog, we place value in our office culture - the relationships that it builds, the creativity it brings to the table, and the collaboration of being together. We operate as a hybrid workplace to ensure our employees can create a work-life harmony that best fits them. Benefits and Growth listed above may vary based on the country of your employment and the nature of your employment with Datadog.

Datadog offers a competitive salary and equity package, and may include variable compensation. Actual compensation is based on factors such as the candidate's skills, qualifications, and experience. In addition, Datadog offers a wide range of best in class, comprehensive and inclusive employee benefits for this role including healthcare, dental, parental planning, and mental health benefits, a 401(k) plan and match, paid time off, fitness reimbursements, and a discounted employee stock purchase plan.

The reasonably estimated yearly salary for this role at Datadog is:

$145,600—$182,000 USD

About Datadog:

Datadog is the leading observability and security platform for the AI era, providing businesses with unified visibility across the technology stack to manage complexity at scale. It brings applications, infrastructure, data, models, and security into one place, using AI to detect and resolve issues before they impact customers. Trusted globally by Fortune 500 companies and high-growth AI leaders, Datadog enables businesses to move faster with clarity and confidence. Learn more about #DatadogLife on Instagram, LinkedIn, and Datadog Learning Center.

Equal Opportunity at Datadog:

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.

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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.