Senior DevOps Engineer (USA)

About DroneDeployDroneDeploy powers field teams with robotics and AI. As the only reality capture platform that combines robotic automation, AI agents, and a truly unified system, DroneDeploy allows critical industries to operate with speed and confidence.From construction and energy to agriculture, the world’s largest companies use DroneDeploy to simplify field operations, improve safety, and make smarter decisions, faster. By combining aerial drones, 360 and fixed cameras, ground robots and proprietary AI, we’re bringing the power of automation and visual intelligence to all stakeholders, from the field to the boardroom.At DroneDeploy, we thrive in a mostly remote-first culture rooted in innovation and impact. We’ve been recognized as a Best Place to Work in the SF Bay Area and named one of America’s Great Places to Work—but what truly sets us apart is the experience you gain: solving real-world challenges with cutting-edge technology, surrounded by teammates who are as passionate as they are supportive. Our team is bold, mission-driven, and building something that matters. We foster a culture where a variety of perspectives drive smart decisions, and where growth—both personal and professional—is part of the journey. Whether it’s flexible schedules, family-friendly benefits, or our strong track record of internal promotions, we invest in people as much as we do in product. If you’re looking to be part of something ambitious, authentic, and transformative, you’ll find your place at DroneDeploy.Role OverviewThe Senior DevOps Engineer is a key member of DroneDeploy’s DevOps organization, partnering closely with software engineering teams to ensure our platform is reliable, scalable, and efficient for customers across construction, energy, agriculture, and other field-based industries.Reporting to the Manager of DevOps, this role focuses on owning complex areas of our cloud infrastructure, leading improvements to our CI/CD pipelines, and building the internal tools that keep code shipping smoothly and safely.This person will operate at the forefront of cloud infrastructure and ML-enabled features, helping to support our primary product and new AI capabilities, including work in ML Ops, model training, and evaluation.This person will operate at the forefront of cloud infrastructure and AI-enabled features, driving the rollout of AI tooling across the organization. You will be instrumental in enabling developer teams to integrate AI into their workflows, managing the end-to-end MLOps lifecycle, and ensuring the robust evaluation and reliability of our primary product’s AI capabilities.They will regularly navigate technical ambiguity, evaluate multiple approaches, and drive projects from design through rollout with limited oversight, shaping reliability, observability, and developer experience across the engineering organization.Work EnvironmentWork Model: Remote (work from home). Time Zone & Collaboration: Collaborate with a distributed DevOps team across US, UK, and New Zealand, with an expectation to overlap at least four hours with US Pacific Time (9 AM – 5 PM) most days and to participate in an on-call rotation for production emergencies.Business Travel: Occasional domestic travel (typically no more than once per quarter) for company events or team gatherings, subject to business needs.AI tooling: Engineering, including DevOps, uses AI tools extensively to boost productivity and quality. This role is expected to actively use AI-assisted coding and analysis tools and to experiment with new AI workflows in areas like CI/CD, observability, and ML Ops so we can measure and raise AI adoption across R&D.ResponsibilitiesOwn key areas of DroneDeploy’s cloud infrastructure, improving reliability, performance, and usability of the platform and related services.Design, build, and evolve infrastructure-as-code to provision and manage scalable, secure environments used across engineering teams.Lead improvements to CI/CD pipelines and release workflows (e.g., GitHub Actions, Jenkins, CircleCI), creating templates and tooling that make deployments faster, safer, and more consistent for product teams.Champion observability by implementing and refining monitoring, logging, alerting, and dashboards that give teams clear visibility into system health and customer impact.Partner with engineers across multiple product areas to streamline code deployment, promote a culture of collaboration and shared responsibility, and define “golden paths” for how services are built, tested, and operated.Identify areas of operational toil or fragility and implement durable automation and process improvements that reduce recurring incidents and support burden.Participate in the production support rotation, including incident response, troubleshooting high-impact issues, and contributing to post-incident reviews and follow‑through actions.Contribute to ML Ops efforts by collaborating with AI-focused teams on running machine learning processes i