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# Technical Product Owner with AI/ML - Hybrid

- **Company:** MSYS Inc.
- **Location:** Dallas, TX, United States
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Agile Methodology, Artificial Intelligence, Amazon Web Services, Confluence, JIRA, Microsoft Azure, Cloud Computing, Continuous Integration, Decision Support Systems, Machine Learning, Scrum Methodology, Chatbots, Large Language Models, Data Analytics, Machine Learning Operations, Microservices
- **Published:** July 12, 2026
- **Apply:** https://www.juju.com/job/00000000gfrr79

## About the Role

+ Experience: 7-10+ years

 + 5-10 years of experience in product ownership/product management or related roles.

 + Strong understanding of AI/ML concepts.

 + Solid knowledge of APIs, microservices, and cloud platforms (AWS, Azure, or GCP).

 + Familiarity with MLOps practices (model deployment, CI/CD, monitoring).

 + Strong experience in Agile/Scrum methodologies.

 + Excellent communication and stakeholder management skills.

Preferred Qualifications

 + Experience in Healthcare domain.

 + Knowledge of GenAI / LLMs (e.g., Chatbots, NLP, OpenAI models).

 + Certification such as Certified Scrum Product Owner (CSPO) or equivalent.

 + Hands-on exposure to tools like JIRA, Confluence, MLflow, etc.

Key Competencies

 + Strong analytical and problem-solving skills

 + Ability to bridge business and technical teams

 + Data-driven decision making

 + Prioritization and roadmap planning

 + Risk assessment and mitigation

## Description

We are seeking a highly skilled Technical Product Owner with AI/ML expertise to drive the development and delivery of data-driven and intelligent solutions. This role requires a blend of product management, technical understanding of machine learning systems, and strong collaboration with engineering, data science, and business teams., + Own and manage the product backlog for AI/ML initiatives, ensuring alignment with business goals.

 + Collaborate with data scientists, ML engineers, and software teams to define product requirements and technical solutions.

 + Translate business needs into AI/ML use cases, user stories, and acceptance criteria.

 + Work closely with stakeholders to define KPIs, success metrics, and model performance benchmarks.

 + Ensure proper handling of data quality, governance, and compliance (especially in regulated domains like healthcare/finance).

 + Participate in sprint planning, backlog grooming, and agile ceremonies.

 + Facilitate communication between technical and non-technical stakeholders.


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