60 Fieldai Software Jobs Hiring Near You

• Drive engineering efforts around a clear deployment-driven roadmap that supports reliable autonomous operation at increasing scale.
• Guide the technical direction and architecture of FieldAI’s software stack, including on-robot systems, cloud services, data pipelines, and operator applications.
• Ensure clear interfaces between autonomy, platform, and application layers to support parallel execution and scale.
• Promote engineering practices that support long-lived, maintainable systems in safety-critical and operational environments.
• Partner with product and autonomy leadership to translate deployment goals into concrete technical milestones and execution plans.

• Lead teams responsible for robotics QA, release processes, and validation pipelines that support predictable and safe software releases.
• Guide development of automated testing infrastructure used for autonomy validation, regression testing, and deployment readiness.
• Oversee autonomy analytics systems that collect, process, and analyze data from real deployments to measure performance, reliability, and system limits.
• Guide software infrastructure efforts including CI/CD, dependency management, developer environments, documentation, and internal tooling.
• Support cloud infrastructure for fleet operations, monitoring, data ingestion, ML workflows, and observability.
• Collaborate with cybersecurity teams to ensure secure operation of on-robot and cloud systems.

• Lead application engineering teams building tools for robot operations, fleet management, mission planning, monitoring, and customer insight.
• Ensure tight integration between robots, cloud services, APIs, and user-facing applications.
• Support development of tools that reduce deployment effort, streamline onboarding, and automate triage and monitoring.Encourage clear separation between rapid operational support and longer-term platform evolution.

• Work with field and operations teams to ensure engineering systems support efficient, repeatable deployments.
• Improve feedback loops from live operations into engineering through metrics, tooling, and structured processes.
• Promote practices that reduce per-deployment engineering involvement over time through automation, documentation, and tooling.
• Support uptime, reliability, and autonomy performance tracking across deployed robots.

• Establish clear planning and execution rhythms that align engineering teams around shared goals and timelines.
• Improve visibility into team capacity, work in progress, and technical dependencies.
• Help teams balance near-term operational needs with longer-term system improvements.
• Support prioritization frameworks that keep engineering effort focused on the highest-impact work.

• Mentor and develop senior engineering leaders across platform and application teams.
• Partner with leadership to shape hiring plans, onboarding processes, and team composition.
• Encourage engineering practices that protect deep technical work while supporting operational needs.Foster a culture of clarity, collaboration, accountability, and continuous improvement.

• 12+ years of experience in software engineering, with significant experience leading multi-team engineering organizations.
• Proven experience delivering and operating complex systems in production or operational environments.
• Strong technical background in distributed systems, infrastructure, reliability engineering, and software quality.
• Experience with robotics, autonomy, embedded systems, or other safety-critical or operationally intensive products.
• Demonstrated ability to work across autonomy, infrastructure, application, and operations domains.
• Strong communication skills and comfort working cross-functionally at the executive level.

• Experience scaling robotic or autonomous systems to broader operations.
• Familiarity with simulation, autonomy validation, and performance analytics.
• Experience working with operational teams, on-call rotations, or live system monitoring.

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.