Sr. Product Manager: AI Automation
New
J
JobgetherTechnology AI
United StatesFull-TimeSenior
Salary100,000 - 180,000 USD per year
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Job Details
- Experience
- 7+ years
- Required Skills
- Artificial IntelligenceCloud ComputingProduct ManagementCI/CDRESTful APIsLLM
Requirements
- 7+ years of experience in product management, technical program management, IT platforms, or related technology leadership roles.
- Proven experience managing intake, prioritization, and delivery of complex internal technology initiatives.
- Strong understanding of software delivery concepts, including CI/CD, cloud environments, authentication, identity management, secrets management, monitoring, and production operations.
- Practical experience with AI and LLM application patterns, including assistants, agents, retrieval systems, and automation workflows.
- Knowledge of AI lifecycle management, including evaluation frameworks, model monitoring, versioning, and regression management.
- Understanding of security and data governance principles, including access controls, data classification, least privilege, and audit requirements.
- Familiarity with responsible AI frameworks and emerging regulations such as NIST AI RMF and EU AI Act.
- Strong communication skills with the ability to align engineers, business stakeholders, and executives.
- Experience managing enterprise software integrations and API-driven platforms is a plus.
- Experience with cloud platforms such as GCP, AWS, or Azure is preferred.
- Background working in regulated or data-sensitive industries such as insurance, finance, healthcare, or similar environments is a plus.
- Experience evaluating AI vendors, SaaS platforms, security requirements, and compliance considerations is preferred.
Responsibilities
- Own the intake and prioritization process for AI applications, automations, and agent requests across multiple business functions.
- Build and maintain a strategic roadmap by evaluating initiatives based on business value, technical feasibility, capacity, risk, and organizational priorities.
- Establish governance standards to ensure AI solutions meet security, compliance, access control, and data protection requirements before production deployment.
- Define quality frameworks for AI solutions, including evaluation criteria, acceptance standards, monitoring processes, and incident response approaches.
- Develop and maintain responsible AI practices, including fairness reviews, explainability requirements, human oversight processes, and alignment with emerging AI regulations.
- Create and improve the operating model that enables business teams to build prototypes while ensuring production-ready solutions meet enterprise standards.
- Lead buy-versus-build evaluations for AI tools, platforms, and vendor solutions in collaboration with security, procurement, and technical teams.
- Partner with engineering teams on cloud platform capabilities, deployment processes, authentication, monitoring, and operational readiness.
- Communicate product strategy, priorities, risks, and progress updates to business leaders and executive stakeholders.
- Define success metrics related to adoption, security posture, production speed, cost efficiency, and business outcomes.
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