Top Engineering Jobs in Boston, MA

Leads engineering teams responsible for Datadog Agent developer experience, build systems, correctness, performance benchmarking, and software supply-chain security. Evolves SDLC practices for a complex multi-language, multi-platform open-source project, including AI coding enablement, CI/CD, build infrastructure, testing, and reliability. Hires, mentors, and develops engineering managers and staff engineers across global teams while balancing velocity, security, and long-term platform investments.

Build and improve software, platforms, and operational frameworks for incident response, on-call readiness, post-mortem learning, and engineering resilience. Lead incident-process design, facilitate reviews, mentor engineers, train on-callers, and drive cross-functional reliability initiatives. The role requires experience with distributed systems, Kubernetes, incident analysis, on-call operations, and software development primarily in Go and Python, with some TypeScript.

Software Engineering Interns contribute to Datadog’s observability and security platform by building and improving backend, frontend, infrastructure, data engineering, and developer tooling systems. Responsibilities include developing distributed and cloud-native services, addressing performance and scalability challenges, delivering technical projects from design through deployment, and collaborating with experienced engineers and mentors.

As a Senior Software Engineer specializing in Distributed Systems, you'll design and implement scalable platforms, optimize data pipelines for durability and low latency, and impactfully contribute to service ownership.

Design and scale high-traffic services, resolve production incidents, deploy features (using feature flags), plan team projects, and improve service performance and architecture at large scale.

Design, build, and operate multi-region, multi-cloud network infrastructure across AWS, GCP, and Azure. Own cloud-to-cloud and customer connectivity, troubleshoot latency/packet-loss via pcap and path analysis, set technical direction for network expansion, improve cross-region connectivity, and identify network cost and efficiency improvements while participating in incident response and on-call rotation.

Build and maintain Bazel-based build, test, and packaging tools for a large monorepo. Improve CI performance and cost efficiency, run complex migrations, keep pipelines reliable, and contribute upstream to the Bazel ecosystem. Own projects end-to-end and collaborate with developers to improve tool usability and developer productivity.

Lead design and implementation of LLM observability features: prototype and scale product capabilities for tracing, evaluating, and debugging generative AI systems. Work cross-functionally to influence architecture, mentor engineers, prioritize customer pain points, and drive product and engineering decisions for reliable, high-performance AI observability.