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DESCRIPTION

DESCRIPTION
AGI Data Services is seeking a seasoned Product Manager - Technical (PMT) to lead our Quality Assessment initiatives. This role will be instrumental in owning and evolving the Quality Assessment Portal (QAP), improving batch-level analytics for workflows, and establishing defined standards for quality strategies and options.

The QAP is a critical tool for evaluating the quality of human-in-the-loop data generated across all channels. It enables AGI-DS to perform Level 1 (L1) quality checks within a two-business day SLA, significantly accelerating feedback cycles with data providers and ensuring scientists have timely access to high-quality data for model training.

Key Responsibilities:

Own and drive the evolution of the Quality Assessment Portal (QAP)

Lead the strategic vision and roadmap for QAP
Collaborate with engineering teams to implement new features and improvements
Ensure the tool meets the evolving needs of scientists and quality assessment teams
Improve batch-level analytics of workflows

Develop and implement strategies to enhance data analysis at the batch level
Work with data scientists and engineers to create more robust and insightful analytics
Drive the integration of advanced analytics into the quality assessment process
Set defined standards for quality strategies and options

Establish comprehensive quality assessment frameworks
Develop and maintain quality metrics and benchmarks
Collaborate with cross-functional teams to ensure alignment on quality standards
Lead cross-functional development teams

Guide teams from design through delivery of quality assessment tools and processes
Influence engineering decisions to build optimal solutions
Ensure scalability and reusability of developed capabilities
Stakeholder management and communication

Regularly communicate with senior management on status, risks, and change control
Collaborate with product management, program management, and partner teams
Present to executive leadership on quality assessment strategies and outcomes
QUALIFICATIONS
Basic Qualifications:

Bachelor's degree in Computer Science, Engineering, or related technical field
7+ years of technical product management experience
5+ years of experience working directly with software engineering teams
Strong understanding of machine learning and data quality concepts
Proven track record of delivering complex technical products
Preferred Qualifications:

Master's degree in Computer Science, Engineering, or related technical field
Experience with quality assessment tools and methodologies in AI/ML contexts
Strong analytical and problem-solving skills, with the ability to translate data insights into actionable strategies
Excellent communication and presentation skills, with the ability to influence senior leadership
Experience in agile development methodologies
Familiarity with data privacy and security best practices

Key job responsibilities
The Sr. Technical Program Manager will interact with product management, program management, cross partner teams, multiple stakeholders and leadership to deliver complex projects and programs. The person will anticipate bottlenecks, provide escalation management, make trade-off decisions, and balance business needs versus technical constraints.
The person should have technical skills to provide solutions, design, build, and deliver it. Successful candidates will have a strong technical background, be detail driven and have excellent problem solving abilities. You will have a deep understanding of product design and implementation details and will successfully represent the technical team to senior leadership and customers. Your technical expertise and operational excellence will influence the team’s decisions and drive secure and robust solutions, which have great customer experience. They are responsible for bridging scientists, technology, process and operations for to achieve the right results. This position defines standards and measurements, identifies the inputs that drive the quality of Ground Truth, and drives initiatives across a variety of teams to achieve these results.


A day in the life
- Collaborate with internal partners to understand their business priorities, communicate outcomes and define roadmaps.
- Define metrics and performance indicators and establish mechanisms to drive them.
- Dive deep into anecdotes and data to find patterns and root causes of problems.
- Dive deep into science, technology and process to identify problems and create solutions. Tirelessly advocate for improvements to systems and processes that will benefit our product teams / stakeholders and business partners.
- Engage with ML Data operations teams to root cause issues, and design solutions.