Manager ll, Engineering - Datadog Agent SDLC
Datadog is hiring a Manager ll, Engineering - Datadog Agent SDLC in Boston and New York, United States. It pays $244k-$305k a year and Level rates it ; you can apply on Datadog.
Level's read on this job
- Works on AI ●●●○ is how Level rates this role: the daily work is on AI products, without building the model.
- Some of the work can be done remotely, according to the posting.
- The posting mentions CI/CD, engineering management and developer experience among its tools and skills.
- Datadog has 433 other open roles on Level.
- Posted within the past two weeks.
AI in this role
Lead engineering teams evolving the Datadog Agent developer experience, build infrastructure, and AI coding enablement.
The Datadog Agent is our flagship open-source project and a critical part of how customers experience Datadog, with hundreds of engineers contributing annually across multiple languages and platforms. As Manager II, Engineering for Datadog Agent SDLC, you will lead the systems, tooling, and developer experience that enable engineers to build, test, secure, and ship software that runs in customer environments. You will guide the evolution of our software development lifecycle as AI coding tools reshape how software is developed, while strengthening our approach to software supply-chain security, build infrastructure, correctness, and performance. This is an opportunity to shape engineering practices for the Agent and establish patterns that can influence other open-source projects across Datadog.
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:
- Lead the engineering teams responsible for the Agent developer experience, build systems, correctness, and performance benchmarking platforms
- Own software supply-chain security for a public repository that ships into customer infrastructure - provenance, signing, dependency and contribution review, and the new risks coding agents introduce
- Evolve the Agent software development lifecycle to support hundreds of contributors while improving developer velocity, reliability, and security
- Drive AI coding enablement across the Agent ecosystem, adapting development workflows and infrastructure as engineers increasingly work alongside coding agents
- Guide the evolution of build infrastructure for a complex, multi-language, multi-platform codebase, including the continued adoption and development of modern build systems
- Hire, mentor, and develop engineering managers and staff engineers across multiple geographies
Who You Are:
- An engineering leader with experience owning software development lifecycle systems and developer infrastructure
- First-hand experience with AI coding tools and flows, excited by the opportunities and mindful of challenges created by AI-assisted software development
- Curious about the art of proving software correct: deterministic simulation testing, fault injection, property-based testing, continuous performance benchmarking
- Familiar with complex multi-language development environments, CI/CD, remote build execution and caching; experience with Bazel or similar build systems is a plus
- Experienced leading multiple teams through technical and organizational change while balancing roadmap velocity, reliability, security, and long-term platform investments
- A proven track record scaling exceptional engineering teams: hiring, coaching, performance management, and building appropriate team structures globally
Datadog values people from all walks of life. We understand not everyone will meet all the above qualifications on day one. That's okay. If you’re passionate about technology and want to grow your skills, we encourage you to apply.
Benefits and Growth:
- High income earning opportunities based on self performance
- New hire stock equity (RSU) and employee stock purchase plan (ESPP)
- Continuous professional development, product training, and career pathing
- Sales training in MEDDIC and Command of the Message
- Intra-departmental mentor and buddy program for in-house networking
- An inclusive company culture, opportunity to join our Community Guilds
- Generous global benefits
Benefits and Growth listed above may vary based on the country of your employment and the nature of your employment with Datadog.
#LI-Hybrid
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:$244,000—$305,000 USDAbout 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.
Datadog endeavors to make our Careers Page accessible to all users. If you would like to contact us regarding the accessibility of our website or need assistance completing the application process, please complete this form. This form is for accommodation requests only and cannot be used to inquire about the status of applications.
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.
How we rate this
Manager ll, Engineering - Datadog Agent SDLC at Datadog rates 65 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.
Works on AI. The daily work is on AI products, without building the model.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Questions you could be asked
- Tell me about a project where engineering management was part of your work. What did you do?
- Tell me about a project where developer experience was part of your work. What did you do?
- Tell me about a project where software development lifecycle was part of your work. What did you do?
- Tell me about a project where build systems was part of your work. What did you do?
- Tell me about a project where supply chain security was part of your work. What did you do?
Adapt your resume
- List these exact terms on your resume: Engineering Management, Developer Experience, Software Development Lifecycle, Build Systems, and Supply Chain Security. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Show where AI is part of your daily process, not a one-off project. This role expects it to be a running habit.
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