Technical Product Manager - Data and AI Platforms

We are seeking a highly skilled and motivated Technical Product Manager - Data & AI Platforms to join our dynamic team. The ideal candidate will have a strong background in product management of data products and platforms, with a proven track record of successfully delivering data-driven products, APIs, and AI/ML enablement capabilities from conception to launch. As a Technical Product Manager, you will be responsible for defining product vision, strategy, and roadmap for data acquisition, labeling, annotation, governance, and quality initiatives, ensuring alignment with business goals and customer needs. You will collaborate closely with cross-functional teams, including engineering, data science, AI/ML, design, marketing, and business stakeholders to deliver high-quality data products and pipelines that power advanced analytics and machine learning solutions.

This role requires 4 - 5 days in client office, located in Dallas, TX.

Perficient is the global AI and technology consulting firm disrupting the traditional consulting model. Powered by our 7,000+ advisors, engineers, and designers, Perficient implements AI-first solutions that break conventions and deliver outcomes that matter. Proudly serving clients that represent the world's most innovative brands, and in collaboration with our powerful technology partner ecosystem, we bring deep industry expertise and data-driven design to redefine how businesses run and succeed. Perficient is different. For real. Learn more at perficient.com.

• Bachelor''s degree in Business, Engineering, Computer Science, Data Science, Information Systems, or a related field; MBA is a plus.
• Minimum of 5 years of experience in Product Management, Data Product Management, or Technical Product Management, with a strong focus on delivering successful data-driven products or platforms.
• Proven experience managing data products, APIs, analytics platforms, or AI/ML enablement solutions from concept through production.
• Strong understanding of the dataset lifecycle, including data acquisition, labeling, annotation, validation, governance, and quality management practices.
• Experience with cloud-based data platforms and modern ETL/ELT architectures in environments such as AWS, Azure, or Google Cloud.
• Proven experience leading cross-functional teams and managing complex technical initiatives involving engineering, data engineering, and data science stakeholders.
• Strong analytical skills, with the ability to assess data quality, interpret performance metrics, and make informed product decisions.
• Excellent communication and interpersonal skills, with the ability to influence and engage stakeholders at all levels.
• Demonstrated ability to think strategically and execute tactically in highly technical and data-intensive environments.
• Experience with Agile methodologies, product management tools, and data-focused delivery frameworks.
• Understanding of data governance, metadata management, lineage, compliance, and data quality frameworks.
• Demonstrated ability to leverage AI tools to enhance productivity, streamline workflows, and support data-informed task execution.
• Familiarity with AI-enhanced platforms, machine learning workflows, and automated data labeling solutions is a plus.
• A solid understanding of AI capabilities and limitations, including ethical considerations, is expected.
• Experience commercializing data products, APIs, or platform capabilities is highly desirable.

ABOUT THE TEAM:

Our Product Development team drives innovation by building digital solutions through a full end-to-end development process. Utilizing modern platforms like Azure, AWS, and Google Cloud Platform, we create customer-focused products, internal workflow tools, and mobile apps that elevate business operations across industries. With a clear focus on results and growth, our team is committed to doubling our global presence while delivering meaningful outcomes for renowned clients. We also embed AI into our solutions to enable smarter features, automate complex workflows, and deliver intuitive, data-driven user experiences.

Our Dallas office isn't just a workplace-it's a thriving community where collaboration, connection, and celebration come together. Through meaningful colleague recognition, active involvement in the local market, and enriching cultural events, we create an environment where every team member feels valued and inspired. You will be joining a supportive network that drives innovation and fosters lasting professional relationships.

Perficient, Inc. proudly provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, gender, sexual orientation, national origin, age, disability, genetic information, marital status, amnesty, or status as a protected veteran in accordance with applicable federal, state and local laws. Perficient, Inc. complies with applicable state and local laws governing nondiscrimination in employment in every location in which the company has facilities. This policy applies to all terms and conditions of employment, including, but not limited to, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation, and training. Perficient, Inc. expressly prohibits any form of unlawful employee harassment based on race, color, religion, gender, sexual orientation, national origin, age, genetic information, disability, or covered veterans. Improper interference with the ability of Perficient, Inc. employees to perform their expected job duties is absolutely not tolerated.

Disability Accommodations: Perficient is committed to providing a barrier-free employment process with reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures. If you need assistance or accommodation due to a disability, please contact us.

Applications will be accepted until the position is filled or the posting is removed.

The salary range for this position takes into consideration a variety of factors, including but not limited to skill sets, level of experience, applicable office location, training, licensure and certifications, and other business and organizational needs. The new hire salary range displays the minimum and maximum salary targets for this position across all US locations, and the range has not been adjusted for any specific state differentials. It is not typical for a candidate to be hired at or near the top of the range for their role, and compensation decisions are dependent on the unique facts and circumstances regarding each candidate. A reasonable estimate of the current salary range for this position is $111,300.00 to $144,600. Please note that the salary range posted reflects the base salary only and does not include benefits or any potential variable compensation programs. Information regarding the benefits available for this position are in our benefits overview.

#LI-GS1. #LI-AiFirst. #LI-TechnicalProdManager

• Define and communicate the product vision and strategy for data products, data pipelines, and AI/ML data capabilities, ensuring alignment with overall business objectives.
• Own and drive the data collection strategy, including ingestion, labeling, annotation, and quality management processes that support machine learning and analytics initiatives.
• Develop and prioritize the product roadmap for data platforms, balancing short-term delivery objectives with long-term scalability, governance, and data quality goals.
• Collaborate with engineering, data engineering, and data science teams to translate product requirements into actionable specifications for ETL/ELT pipelines, cloud data platforms, and data services.
• Lead cross-functional teams through the end-to-end product lifecycle, ensuring timely delivery of high-quality data products, APIs, and platform capabilities.
• Establish and monitor data quality frameworks, governance standards, quality gates, and performance metrics to ensure reliability, accuracy, and usability of datasets.
• Gather and analyze feedback from internal stakeholders, customers, and AI/ML teams to drive continuous product improvements and data quality enhancements.
• Monitor product performance, adoption, and operational metrics, making data-driven decisions to optimize data assets and platform capabilities.
• Act as the primary point of contact for data product initiatives, fostering strong relationships with stakeholders across engineering, operations, analytics, and business functions.
• Stay up-to-date with evolving technologies and best practices related to cloud data platforms, data governance, machine learning enablement, sensor data collection, auto-labeling, and data product commercialization.
• Partner with teams supporting sensor kits and pods, HLOG conversion, MCAP data management, and automated labeling initiatives to ensure scalable, high-quality data operations.
• Define and communicate the product vision and strategy for data products, data pipelines, and AI/ML data capabilities, ensuring alignment with overall business objectives.
• Own and drive the data collection strategy, including ingestion, labeling, annotation, and quality management processes that support machine learning and analytics initiatives.
• Develop and prioritize the product roadmap for data platforms, balancing short-term delivery objectives with long-term scalability, governance, and data quality goals.
• Collaborate with engineering, data engineering, and data science teams to translate product requirements into actionable specifications for ETL/ELT pipelines, cloud data platforms, and data services.
• Lead cross-functional teams through the end-to-end product lifecycle, ensuring timely delivery of high-quality data products, APIs, and platform capabilities.
• Establish and monitor data quality frameworks, governance standards, quality gates, and performance metrics to ensure reliability, accuracy, and usability of datasets.
• Gather and analyze feedback from internal stakeholders, customers, and AI/ML teams to drive continuous product improvements and data quality enhancements.
• Monitor product performance, adoption, and operational metrics, making data-driven decisions to optimize data assets and platform capabilities.
• Act as the primary point of contact for data product initiatives, fostering strong relationships with stakeholders across engineering, operations, analytics, and business functions.
• Stay up-to-date with evolving technologies and best practices related to cloud data platforms, data governance, machine learning enablement, sensor data collection, auto-labeling, and data product commercialization.
• Partner with teams supporting sensor kits and pods, HLOG conversion, MCAP data management, and automated labeling initiatives to ensure scalable, high-quality data operations.