Product Manager

TEKsystems Global Services (TGS) is a growth solution for enterprises, focusing on technology, strategy, and operations. The Product Manager - Data Operations is responsible for the execution and management of enterprise AI data consulting engagements, ensuring high-quality delivery and operational efficiency.

Responsibilities:

• Execute the daily "flywheel" of data ingestion and delivery, actively manage annotation queues, monitor throughput velocities, and identify "blocked" tasks to ensure continuous data flow between client buckets and labeling platforms
• Implement and track the evaluation success metrics (KPIs) defined by the strategic roadmap. Generate daily and weekly reports on model performance, annotator efficiency, and data distribution to provide actionable insights to Research and Engineering stakeholders
• Maintain and version-control complex prompt libraries used for Red Teaming and model stress-testing. Ensure that "Jailbreak" and "Safety" datasets are up-to-date and correctly tagged for regression testing
• Continuously analyze operational data to identify bottlenecks in the labeling workflow. Configure and refine tooling workflows (e.g., Labelbox, Scale, custom UIs) to improve annotator ergonomics and reduce time-per-task (TPT). Identify new product opportunities and manage the product innovation process
• Act as the operational "Managing Editor," translating high-level rubric guides into concrete, enforceable rules for annotators. Update guidelines in real-time based on edge cases and client feedback to ensure consistent tone and factual accuracy
• Oversee the daily quality framework. Monitor Inter-Rater Reliability (IRR) scores, conduct root-cause analysis on disagreements, and manage "Arbitration" queues to resolve complex edge cases
• Own the project RAID log (Risks, Assumptions, Issues, Dependencies). Proactively identify operational risks (e.g., vendor tool outages, low worker supply) and communicate mitigation plans to the PM - Data Ops Lead and client leadership
• Maintain the project "Knowledge Base," ensuring that all delivery methodologies, decision logs, and technical SOPs are documented, understood, and followed by the delivery team from initiation to closeout. And update key artifacts reflecting continuous improvements and lessons learned
• Serve as the primary point of contact for Client TPM Leads and Forward Deployed Engineering Leads regarding daily status, blockers, and sprint planning. Ensure a "No Surprises" culture through transparent and frequent communication
• Assist sales and strategic teams by providing data-driven estimates for effort, timeline, and resource requirements. Lead "Proof of Concept" (POC) executions to demonstrate operational capability to prospective clients

Requirements:

• Bachelor's degree in Computer Science, Linguistics, Data Analytics, or a related technical field, or equivalent practical experience
• Approximately 3–7 years of experience in technical program management, product operations, or enterprise service delivery, with specific experience in data-intensive or AI/ML environments
• Hands-on experience with data annotation platforms, editorial workflows, or managing operational teams (e.g., support ops, trust & safety, content moderation)
• Strong Sheets/Excel/Tableau skills for reporting; familiarity with JSON/Python for data handling is a strong plus. Excellent technical judgement
• Proven ability to manage sprint schedules, unblock technical teams, and maintain high quality under tight deadlines
• Experience acting as a Team Lead or Operations Manager for large groups of knowledge workers (writers, annotators, analysts)
• AI/Data Certification, Certifications in Data Analytics, Agile (CSM, PSM), or CAPM (Certified Associate in Project Management)
• Prompt Engineering Familiarity, understanding of LLM prompting techniques (Chain-of-Thought, Few-Shot) and common failure modes (hallucinations, bias)
• Experience configuring and managing projects in tools like Jira, Linear, Labelbox, Scale AI, or similar HITL platforms
• Proficiency in multiple languages is a plus for global model evaluation projects
• Experience with AI product management