Staff Software Engineer - Watchdog Anomaly Detection
Datadog is hiring a Staff Software Engineer - Watchdog Anomaly Detection in 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
- On Level's scale, this software engineer role is Works on AI ●●●○: the daily work is on AI products, without building the model.
- The listed pay starts 45% above the typical software engineer posting on Level.
- Tools and skills the posting cites include Distributed Systems, Streaming and Batch Processing.
- Level lists 433 other open roles at Datadog.
- The role was posted within the past week.
AI in this role
Lead the architecture and evolution of large-scale distributed systems and data pipelines powering automated anomaly detection platforms.
Datadog is looking for a Staff Software Engineer to help shape the future of our anomaly detection platform. Our team builds and operates high-scale distributed systems that process streaming and batch data, working alongside machine learning systems to automatically identify potential issues in our customers' environments. As we expand these capabilities across Datadog's products, you'll play a key role in defining the technical direction, evolving our architecture, and building systems that surface meaningful insights to customers without requiring manual configuration. This is an opportunity to solve complex engineering challenges at scale while influencing the direction of a platform that powers critical customer experiences.
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 architecture and evolution of large-scale distributed systems that power automated anomaly detection across Datadog's platform.
- Design and improve high-throughput streaming and batch processing pipelines, enabling timely and reliable detection of potential issues in customer environments.
- Drive technical initiatives to simplify, consolidate, and modernize existing systems, improving scalability, maintainability, and operational efficiency.
- Partner with engineering leaders, product managers, and data scientists to define the long-term technical strategy for anomaly detection and its integration with alerting capabilities.
- Shape how anomaly detection capabilities are delivered across Datadog products, helping customers identify meaningful issues without requiring manual configuration.
- Provide technical leadership across engineering teams, influencing architectural decisions and aligning solutions with broader product and platform goals.
Who You Are:
- You have extensive experience designing, building, and operating large-scale distributed systems, particularly high-throughput or data-intensive backend platforms.
- You have a strong understanding of streaming and batch processing architectures, including the challenges of processing large volumes of data with low latency.
- You have experience leading complex architectural initiatives, making technical tradeoffs, and improving the reliability and maintainability of production systems.
- You can drive technical strategy beyond your immediate team, collaborating with engineering leaders and product partners to translate customer needs into scalable platform solutions.
- You are comfortable working across technologies and learning new systems; experience with technologies such as Flink, Kafka, Cassandra, Go, or Python is a plus.
- You bring a product-oriented mindset and can connect technical decisions to customer outcomes; familiarity with machine learning systems or deploying models in production is a plus, but not required.
- Generous and competitive benefits package
- New hire stock equity (RSUs) and employee stock purchase plan (ESPP)
- Continuous career development and pathing opportunities
- Employee-focused best in class onboarding
- Internal mentor and cross-departmental buddy program
- Friendly and inclusive workplace culture
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
Staff Software Engineer - Watchdog Anomaly Detection 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
Also common in software engineer jobs at this level
Pay
- This job starts at
- $244k
- Typical software engineer job
- $168k
This posting starts 45% above the typical software engineer job. See software engineer jobs
Questions you could be asked
- What's a project where you used Distributed Systems hands-on?
- Walk me through how you've used Streaming in your day-to-day work.
- What are the limits of Batch Processing that you've run into, and how did you work around them?
- Describe a typical day in a role like this one: which parts run through AI directly?
- If you removed AI from this role, what would be left, and how do you decide what still needs a human?
Adapt your resume
- List these exact terms on your resume: Distributed Systems, Streaming, and Batch Processing. 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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