Senior Software Engineer - Bits AI SRE

We're a new team building AI-assisted product experiences that help Datadog customers go from investigation to action, by enabling conversational workflows, guided remediations, and codefixes that address the root cause of production issues. We're looking for a product-minded engineer to help us quickly define and ship applied AI experiences across chat, remediations, and codefixes. This role sits at the intersection of backend engineering, product development, and prompt engineering, with a strong emphasis on building reliable, production-quality AI systems. 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: - Work closely with product managers, designers, and engineers to build and iterate on AI-powered product experiences in Bits AI SRE. - Develop customer-facing systems across chat, remediations, and codefixes that help users resolve production issues more quickly. - Work on prompts, evaluation loops, and backend systems to make applied AI workflows reliable, useful, and production-ready. - Prototype quickly, test what works in the real world, and iterate rapidly to ship new product capabilities. - Build the infrastructure and product logic needed to connect AI outputs to meaningful actions, including operational remediations and generated code changes. - Collaborate with partner teams across Datadog to expand remediation capabilities and integrate with systems that support investigation, automation, and code generation. - Follow the latest developments in LLM prompting, agent design, and applied AI product development, and bring strong judgment about what is practical to use in production. Who You Are: - You're an engineer with at least 5 years of professional experience, with strong backend engineering skills and a product mindset. You have experience building production systems in Go (or similar) and have worked with LLM-based systems in practice. - You are excited about applied AI and motivated by building product experiences that help users take meaningful action, not just generate insights. - You have experience with prompt engineering, evaluation, and iteration for LLM-powered systems, and know how to improve quality through experimentation and feedback. - You have strong engineering fundamentals and can build the systems needed to productionize AI features, including integrating model behavior into reliable user-facing products. - You are comfortable operating in a fast-moving environment with high ambiguity, and enjoy prototyping, learning quickly, and shipping early versions of new ideas. - You collaborate well with cross-functional partners and can work effectively with product, design, and engineering to shape both the user experience and the technical implementation. - You care about product quality and user outcomes, and can balance speed with pragmatism when building new AI-powered workflows. - Bonus: you have experience with Kubernetes or systems related to production remediation and operational automation. - Requirement - Demonstrated ability to use AI coding tools in day-to-day workflows and validate, critique, and refine AI-generated output. - Plus - You’re motivated to push the boundaries of how AI can improve software engineering best practices and contribute to building AI-enabled products. 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: - Get to build tools for software engineers, just like yourself. And use the tools we build to accelerate our development. - Have a lot of influence on product direction and impact on the business. - Work with skilled, knowledgeable, and kind teammates who are happy to teach and learn. - Competitive global benefits. - Continuous professional development. Benefits and Growth listed above may vary based on the country of your employment and the nature of your employment with Datadog. To conform to US export control regulations, candidates should be eligible for any required authorizations from the US government. This job is available in various departments within our company; to conform to US export control regulations, some of these roles may require candidates to be eligible for any required authorizations from the US government. #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 health

You're an engineer with at least 5 years of professional experience, with strong backend engineering skills and a product mindset. You have experience building production systems in Go (or similar) and have worked with LLM-based systems in practice. You are excited about applied AI and motivated by building product experiences that help users take meaningful action, not just generate insights. You have experience with prompt engineering, evaluation, and iteration for LLM-powered systems, and know how to improve quality through experimentation and feedback. You have strong engineering fundamentals and can build the systems needed to productionize AI features, including integrating model behavior into reliable user-facing products. You are comfortable operating in a fast-moving environment with high ambiguity, and enjoy prototyping, learning quickly, and shipping early versions of new ideas. You collaborate well with cross-functional partners and can work effectively with product, design, and engineering to shape both the user experience and the technical implementation. You care about product quality and user outcomes, and can balance speed with pragmatism when building new AI-powered workflows. Bonus: you have experience with Kubernetes or systems related to production remediation and operational automation. Requirement - Demonstrated ability to use AI coding tools in day-to-day workflows and validate, critique, and refine AI-generated output. Plus - You’re motivated to push the boundaries of how AI can improve software engineering best practices and contribute to building AI-enabled products.