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Datadog is building a new team focused on AI-assisted developer tools that autonomously generate tests, fix bugs, and improve performance. This role is for a product-minded backend engineer to help define and ship products that make Datadog customers 10x more effective developers.
You will work closely with users, designers, product managers, and data scientists to build cutting-edge LLM-based agents. Your responsibilities include working on prompts, evaluations, and agent tools for code-related tasks, as well as the engineering required to productionize these systems and integrate them with Datadog's platform. You'll prototype solutions, validate them in the real world, iterate with users, and ship features.
You'll stay current with the latest research on LLM prompting, agents, and code editing. You'll also collaborate with other Datadog teams to expand capabilities—for example, integrating with Datadog IDE extensions to deliver a CoPilot-like assistant, or leveraging Dynamic Instrumentation to collect runtime data from production and pre-production environments.
You bring at least 5 years of professional backend engineering experience (Go, Java, Python), with a track record of shipping software that uses LLMs in production. You're passionate about generative AI and its potential to boost developer productivity. You have relevant experience with large language models, large-scale systems and datasets, machine learning, or adjacent fields. You're an excellent communicator who can drive technical conversations toward pragmatic solutions. You have experience building developer tools such as IDEs, static code analysis tools, or compilers. You actively use AI coding tools in your workflow and can validate, critique, and refine AI-generated output. You value code simplicity and performance, and you thrive in fast, high-growth startup environments that respect engineers and customers.
