Engineering Manager, Data Analytics (AI Reliability)

Who we are:

Motive empowers the people who run physical operations with tools to make their work safer, more productive, and more profitable. For the first time ever, safety, operations and finance teams can manage their drivers, vehicles, equipment, and fleet related spend in a single system. Combined with industry leading AI, the Motive platform gives you complete visibility and control, and significantly reduces manual workloads by automating and simplifying tasks.

Motive serves more than 100,000 customers – from Fortune 500 enterprises to small businesses – across a wide range of industries, including transportation and logistics, construction, energy, field service, manufacturing, agriculture, food and beverage, retail, and the public sector.

Visit gomotive.com to learn more.

About the Role:

We’re looking for an experienced and impact-driven Engineering Manager to lead a newly formed team focused on the reliability, robustness, and performance of our AI features and services. This team will play a critical role in ensuring our AI-powered features operate with high precision and consistency in production environments.

You will be responsible for building and growing a team of engineers and analysts focused on data analysis, debugging, root-causing production issues, and figuring out the long tail of failures and corner cases across our AI stack. You’ll partner closely with applied AI teams, product engineering, QA, customer success, and customer support to close the loop between real-world usage and in-field behavior and the performance of our AI systems.

Responsibilities:

• Build, manage, and mentor a high-performing engineering team focused on AI system reliability.
• Lead efforts to detect, diagnose, and mitigate failures and degradation across AI features in production.
• Design tools, dashboards, and processes to surface anomalies, performance regressions, and edge cases.
• Drive cross-functional initiatives to improve monitoring, observability, and data quality.
• Oversee data analysis, annotation processes, and AI system workflows to improve model performance.
• Develop and maintain technical documentation for AI workflows, ensuring clarity and efficiency.
• Monitor key AI performance metrics and implement strategies for optimization.
• Champion a culture of ownership, rigor, and continuous learning within the team.
• Actively coordinate and share data insights with the research groups within Motive to improve product and customer experience.

Requirements:

• 2+ years of experience managing high-performing engineering teams, preferably in AI, ML infrastructure, or production systems.
• Strong understanding of AI feature development lifecycles, data pipelines, model debugging, and post-deployment validation.
• Proven experience with root cause analysis, reliability engineering, or debugging complex distributed systems.
• Strong analytical mindset and ability to dig deep into data to uncover insights.
• Experience working cross-functionally with ML researchers, product managers, customer success and support teams, and data engineers.
• Excellent communication and leadership skills; ability to drive clarity in ambiguous environments.
• Proficiency in Python and SQL for data processing and reporting.
• Flexible to work across PK - US time zones

Creating a diverse and inclusive workplace is one of Motive's core values. We are an equal opportunity employer and welcome people of different backgrounds, experiences, abilities and perspectives.

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The applicant must be authorized to receive and access those commodities and technologies controlled under U.S. Export Administration Regulations. It is Motive's policy to require that employees be authorized to receive access to Motive products and technology.