AI System Reliability Lead

5 days ago

Sargodha, Punjab, Pakistan beBeeEngineering Full time $153,375 - $240,625
As an AI Engineering Manager, you will be responsible for leading a 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.This is a key leadership opportunity to build and grow a team of engineers and analysts who are passionate about data analysis, debugging, root-causing production issues, and figuring out the long tail of failures and corner cases across our AI stack.You will lead efforts to detect, diagnose, and mitigate failures and degradation across AI features in production. Additionally, you will design tools, dashboards, and processes to surface anomalies, performance regressions, and edge cases.The ideal candidate will have at least 2 years of experience managing high-performing engineering teams, preferably in AI, ML infrastructure, or production systems. A strong understanding of AI feature development lifecycles, data pipelines, model debugging, and post-deployment validation is also essential.We offer a diverse and inclusive workplace environment where creativity and innovation thrive. We value collaboration, open communication, and mutual respect among team members.Key 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.
Requirements:
  • A minimum of 2 years of experience managing high-performing engineering teams, preferably in AI, ML infrastructure, or production systems.
  • A 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.
  • A 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.
  • Flexibility to work across time zones.

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