Suggested rewrite: Led a cross-functional initiative that improved [business outcome] by [measurable result], demonstrating experience relevant to this role...
Senior Developer Advocate – Modern App Development
- Remote from
- USA
- Salary
- USD 172k–215k / yr
- Department
- Software Engineering
- Employment
- Full Time
- Experience
- Senior
- Published
- Apply before
- 12 Dec 2026
- Listing views
- 33
- Application actions
- 3
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About this role.
We are a team of engineers that translate our real-world experience to help our user communities solve problems. With a focus on AI-accelerated workflows and next-generation developer ecosystems, you will have the opportunity to meet fast-moving teams where they are, helping them lay strong engineering foundations and broadening your impact to the developer community at large. This is a unique opportunity to use both your engineering depth and authentic storytelling skills to shape how the next wave of builders approach software health, scalability, and observability.
What You’ll Do:
- Help developers hone their craft in an AI-accelerated world by exploring how AI coding assistants and rapid-prototyping tools change software workflows, and guiding teams on how to balance rapid prototyping with established engineering practices around performance, code health, and system reliability.
- Build in public by creating authentic, peer-to-peer technical content, sharing your engineering insights directly where modern developers collaborate in person and online.
- Drive a constructive, bidirectional feedback loop between fast-moving developer communities and our internal teams, translating real-world developer experiences into actionable product insights to shape our roadmap while advocating for user needs from the inside.
- Design and ship high-quality open-source boilerplate templates, quickstarts, and tools that make integrating observability seamless across AI native workflows, next-gen platforms (Vercel, Supabase, etc.), and cloud providers (AWS, GCP, Azure).
Who You Are:
- A builder with approximately 10+ years of software engineering experience, ideally having shipped applications from scratch or worked within an early-stage startup environment where you’ve worn multiple hats.
- An AI-fluent developer who natively leverages AI coding assistants and rapid-prototyping tools as a core part of your regular, day-to-day development workflow.
- Multi-stack familiar, comfortable writing and debugging code across multiple programming languages (such as JavaScript/TypeScript or Python) and experienced with deployment paradigms spanning next-gen platforms and traditional cloud ecosystems.
- An authentic communicator with approximately 3+ years of experience in technical storytelling and community engagement, backed by a publicly available portfolio of peer-to-peer artifacts like GitHub repositories, technical blogs, video walkthroughs, or public speaking presentations.
- A forward thinker who loves self-driven exploration of emerging technologies, and is deeply passionate about developer education, mentorship, and helping other engineers hone their craft.
Bonus points:
- Active community presence or leadership: You are an active participant, contributor, or moderator in developer spaces (such as meetups, Discord, Reddit, or open-source ecosystems focused on next-gen tech).
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:
- New hire stock equity (RSUs) and employee stock purchase plan (ESPP)
- Continuous professional development, product training, and career pathing
- Intradepartmental mentor and buddy program for in-house networking
- An inclusive company culture, ability to join our Community Guilds (Datadog employee resource groups)
- Access to Inclusion Talks, our Internal panel discussions
- Free, global mental health benefits for employees and dependents age 6+
- Competitive 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-Remote
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:
$172,000—$215,000 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.
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.
This job listing has been manually reviewed by the Jobicy Trust & Safety Team for compliance with our posting guidelines, including verification of the company's legitimacy, accuracy of job details, clarity of remote work policy, and absence of misleading or fraudulent content.
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Sample interview questions
I would establish baseline measures for delivery speed, review cycle time, defect rates, test coverage, and production reliability. I would then run a controlled adoption period, pair the tooling with clear review and testing practices, and collect qualitative developer feedback. The goal is to identify where AI accelerates routine work while retaining engineering controls for architecture, security, and maintainability.
I would begin with a concrete developer problem and build a minimal, runnable reference application that demonstrates instrumentation, useful dashboards, and a troubleshooting workflow. The repository would include clear setup instructions, secure configuration examples, automated tests, and deployment guidance. I would validate it with developers unfamiliar with the product and iterate based on the points where they struggle.
I synthesize recurring feedback into themes, preserve representative examples, and distinguish feature requests from underlying user problems. I prioritize insights using frequency, customer impact, strategic relevance, and implementation context. I then present actionable findings to product and engineering partners and close the loop publicly when improvements are made.
Credible content is specific, technically accurate, reproducible, and honest about trade-offs. It should be built from real implementation experience rather than marketing claims, include code or practical examples, and explain when a recommended approach may not fit. Peer review and public feedback are valuable mechanisms for maintaining trust.
I would advocate for developers by communicating their needs clearly and accurately inside the company, while externally sharing guidance that is useful even when it includes constraints or trade-offs. I would avoid overstating product capabilities and maintain transparency when a workflow has limitations. Trust is built by being technically honest, responsive, and consistent across both audiences.
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