Tech Lead Manager, Fleet Management

Cobot•Santa Clara, CA

54d•$215,000 - $245,000•Onsite

About The Position

Do you love building the systems that connect intelligent robots to the cloud? At Cobot, we’re creating the software backbone that powers our fleet — and we’re looking for a Tech Lead Manager, Fleet Management to help us lead the way. This is your opportunity to design and scale the cloud infrastructure that keeps our robots connected, coordinated, and performing in the real world. In this role, you’ll lead the architecture and development of our off-robot software stack — from fleet management and telemetry to APIs and data services. You’ll work closely with autonomy, operations, and platform teams to build reliable, secure, and scalable systems that bridge our robots and the cloud. Along the way, you’ll mentor engineers, shape technical strategy, and define how data flows across every level of the organization. This is a chance to take ownership of the cloud platform that enables real-time insights, efficient operations, and large-scale deployment of collaborative robots. If you’re excited to define how intelligent machines connect to the world — and to lead a team making that vision real — we’d love for you to join us. This role is located at our Santa Clara, CA headquarters.

Requirements

Bachelor’s degree in Computer Science or a related technical field.
5+ years of experience working within engineering teams.
Experience in Rust, Python, c++ or willingness to learn other languages.
Expertise in cloud infrastructure (AWS, GCP, or Azure) — including compute orchestration, networking, and data storage.
Proven ability to design and maintain high-availability distributed systems with strong observability (metrics, logs, tracing).
Deep understanding of API design (REST, gRPC, or GraphQL) and secure data exchange between systems.
Familiarity with real-time or near-real-time messaging frameworks (MQTT, Kafka, Pub/Sub, or WebSockets).
Experience with CI/CD pipelines, containerization (Docker, Kubernetes), and cloud-native deployment practices.
Strong foundation in data modeling, telemetry pipelines, and analytics integration.
Excellent communication and leadership skills, with the ability to collaborate across hardware, autonomy, and operations teams.
Willing to occasionally travel.
Must have and maintain US work authorization.

Nice To Haves

8+ years of software engineering experience.
Advanced degree (Master’s or PhD) in Computer Science, Computer Engineering, or Electrical Engineering or similar field.
Experience developing robotics cloud platforms or IoT fleet management systems.
Familiarity with ROS-based data flows and robot-to-cloud communication architectures.
Knowledge of security and compliance standards (e.g., ISO 27001, SOC 2, GDPR).
Exposure to data visualization, analytics dashboards, or ML model deployment for robot performance insights.
Experience operating production systems with large distributed fleets of connected devices.

Responsibilities

Lead the architecture and development of our off-robot software stack — including fleet management services, telemetry ingestion, and customer-facing APIs.
Design and implement APIs and SDKs for integration with external systems, partner portals, and data analytics platforms.
Develop the cloud platform for robot lifecycle management — including provisioning, configuration, health monitoring.
Ensure reliability and observability across the fleet through robust logging, monitoring, and alerting systems.
Collaborate with autonomy and operations teams to define data flows between robots and backend systems, ensuring low latency and high availability.
Guide the design of the data pipeline for real-time and historical analysis, enabling insights into robot performance, utilization, and behavior.
Mentor and lead engineers fostering a culture of reliability and technical excellence.
Contribute to system security and compliance, ensuring data integrity, access control, and resilience against failures.
Represent the off-robot platform in cross-functional discussions, aligning long-term technical strategy with product and business goals.