Staff Software Engineer
Job description
About the role
Staff Software Engineer, Logs Organization
We are seeking a Staff Software Engineer to lead critical advancements in our logs organization. This position involves owning complex initiatives that span from raw log intake through to observable insights. You will be responsible for redefining how ingestion pipelines, search infrastructure, and intelligent management capabilities operate. The role demands pushing technical boundaries, particularly in the areas of AI and distributed systems, while guiding long-term strategy.
The work environment is hybrid, supporting a culture of collaboration and creativity. Datadog values the relationships built through this structure and the innovation it fosters.
What You'll Do
You will be responsible for architecting and driving complex initiatives that define the future of log management. This involves owning the entire lifecycle of log pipelines, ensuring data moves reliably from ingestion to query execution. You will design the architecture for search infrastructure, balancing the need for high query performance against scalable ingestion demands.
A key focus will be exploring and prototyping new AI-powered log management capabilities. This work will be done in close collaboration with security and business operations teams. You will also explore external data sources to expand the range of observability signals available to customers.
Defining product strategy will be a core responsibility. You will work directly with product managers and customer feedback to guide direction and ensure impactful features are delivered. also, you will mentor engineers across various levels, fostering a culture of high quality outcomes and collaboration within the team.
A significant portion of the role involves validating AI-generated output and refining models to ensure accuracy and reliability in production environments. You will champion best practices for AI-enabled software engineering specifically within log management systems.
Who You Are
The ideal candidate brings deep experience in backend systems, with a specific focus on data-intensive and distributed infrastructure. You must excel in ambiguous environments, demonstrating drive, curiosity, and pragmatic decision-making skills.
You have a history of partnering with product managers and customers to define product direction and successfully ship features. Your experience includes debugging complex systems and consistently optimizing the performance of real-time data pipelines.
You have experience using AI agent tools in your daily engineering work and validate the results these tools produce. Leading by example is a core part of your philosophy; you enjoy helping others grow through mentorship and collaboration. You have used AI coding tools in your daily workflow and possess the ability to validate and refine their output effectively.
Compensation and Location
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Location: USA
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Engagement: Hybrid
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Compensation: $244,000-$305,000 USD
Benefits and Growth
Datadog offers a competitive and comprehensive benefits package. This includes new hire stock equity via our stock option and employee stock purchase plan. You will have access to continuous career development and pathing opportunities. Our onboarding program is designed to be best in class and employee-focused, supported by an internal mentor and cross-departmental buddy program.
Benefits and growth details listed above may vary based on the country of employment and the nature of your employment with Datadog.
About Datadog
Datadog values people from all walks of life. We understand not everyone will meet all the above qualifications on day one. That is acceptable. If you are passionate about technology and want to grow your skills, we encourage you to apply.
Requirements
- Meet the bar Practical notes
About the company
Datadog delivers an observability service for cloud-scale applications. Teams use the platform to monitor servers, databases, tools, and services through a SaaS-based data analytics platform. Roles span product, engineering, design, and operations.
Collaboration happens across teams that build and support the platform. You contribute to feature development, reliability, and usability. The company maintains a publicly traded listing on the Nasdaq stock exchange.