Job description

Role : Sr Technical Product Owner/Product Mgr (Gen/Agentic AI Sol) Location : Charlotte NC (Onsite) Rate : $68 (do not exceed) Role Overview As a Senior Technical Product Owner/ Product Manager for GenAI Solutions, you will bridge the gap between complex business challenges and cutting-edge artificial intelligence. You will partner with business teams from problem framing through release , owning the end-to-end product lifecycle for our next-generation AI initiatives. In this role, you will be the driving force behind defining, building, and deploying scalable, enterprise-grade AI products. You will own the intake, prioritization, backlog, acceptance criteria, KPIs, governance readiness, and adoption outcomes for solutions powered by Large Language Models (LLMs) and advanced agentic architectures. Key Responsibilities • Product Strategy & Intake: Partner with cross-functional business units to frame problems, evaluate feasibility, and Client high-value opportunities for generative AI application. • Backlog & Execution Management: Define, manage, and prioritize the product backlog. Write clear feature requirements, user stories, and strict acceptance criteria. • Solution Delivery & Adoption: Drive the end-to-end product lifecycle from proof-of-concept (PoC) to production release, ensuring high user adoption and clear business value alignment. • KPI & Performance Tracking: Establish and monitor product success metrics, business KPIs, and technical evaluation standards to measure impact and continuous performance improvement. • Governance & Risk Control: Partner with legal, compliance, and risk teams to ensure all solutions satisfy responsible AI principles, data privacy laws, and model-risk controls. • Executive Communication: Present product roadmaps, project statuses, risks, and ROI metrics clearly to senior leadership and technical stakeholders. Required Skills & Qualifications Core Product Management • Product Management: Proven experience managing complex technical products in an agile environment. • Backlog Management: Expertise in backlog grooming, user story creation, and release mapping using tools like Jira or Azure DevOps. • Executive Communication: Ability to translate deep technical AI concepts into simple, business-oriented language for executive stakeholders. Generative AI & Technical Expertise • Agentic Solution Design: Conceptual understanding of designing autonomous, multi-agent AI systems, tool use (function calling), and complex reasoning workflows. • LLMs and RAG: Deep familiarity with building applications using Large Language Models and Retrieval-Augmented Generation (RAG) architectures. • Model Selection: Ability to evaluate and select the right model for the job (e.g., commercial vs. open-source, frontier models vs. task-specific fine-tuned models) based on cost, latency, and accuracy. • Evaluation Metrics: Experience establishing evaluation frameworks for GenAI systems, leveraging both automated metrics (e.g., ROUGE, BLEU, RAGAS) and human-in-the-loop validation. Governance & Ethics • Responsible AI & Model-Risk Controls: Deep understanding of AI vulnerabilities (e.g., hallucination mitigation, prompt injection, data drift) and experience implementing guardrails for safe deployment. Preferred Qualifications • Bachelor's or Master's degree in Computer Science, Data Science, Engineering, or a related technical field (or equivalent practical experience). • 5+ years of software product management experience, with at least 2+ years dedicated to AI/ML or Generative AI products. • Experience collaborating with enterprise data engineering and cloud infrastructure teams (AWS, Azure, or GCP).

Requirements

Must-haves

Role : Sr Technical Product Owner/Product Mgr (Gen/Agentic AI Sol)
Location : Charlotte NC (Onsite)
Rate : $68 (do not exceed)
Product Strategy & Intake: Partner with cross-functional business units to frame problems, evaluate feasibility, and Client high-value opportunities for generative AI application.
Backlog & Execution Management: Define, manage, and prioritize the product backlog. Write clear feature requirements, user stories, and strict acceptance criteria.
Solution Delivery & Adoption: Drive the end-to-end product lifecycle from proof-of-concept (PoC) to production release, ensuring high user adoption and clear business value alignment.
KPI & Performance Tracking: Establish and monitor product success metrics, business KPIs, and technical evaluation standards to measure impact and continuous performance improvement.
Governance & Risk Control: Partner with legal, compliance, and risk teams to ensure all solutions satisfy responsible AI principles, data privacy laws, and model-risk controls.
Executive Communication: Present product roadmaps, project statuses, risks, and ROI metrics clearly to senior leadership and technical stakeholders.
Required Skills & Qualifications
Core Product Management
Product Management: Proven experience managing complex technical products in an agile environment.
Backlog Management: Expertise in backlog grooming, user story creation, and release mapping using tools like Jira or Azure DevOps.
Executive Communication: Ability to translate deep technical AI concepts into simple, business-oriented language for executive stakeholders.
Generative AI & Technical Expertise
Agentic Solution Design: Conceptual understanding of designing autonomous, multi-agent AI systems, tool use (function calling), and complex reasoning workflows.
LLMs and RAG: Deep familiarity with building applications using Large Language Models and Retrieval-Augmented Generation (RAG) architectures.
Model Selection: Ability to evaluate and select the right model for the job (e.g., commercial vs. open-source, frontier models vs. task-specific fine-tuned models) based on cost, latency, and accuracy.
Evaluation Metrics: Experience establishing evaluation frameworks for GenAI systems, leveraging both automated metrics (e.g., ROUGE, BLEU, RAGAS) and human-in-the-loop validation.
Governance & Ethics
Responsible AI & Model-Risk Controls: Deep understanding of AI vulnerabilities (e.g., hallucination mitigation, prompt injection, data drift) and experience implementing guardrails for safe deployment.

Nice-to-haves

Bachelor's or Master's degree in Computer Science, Data Science, Engineering, or a related technical field (or equivalent practical experience).
5+ years of software product management experience, with at least 2+ years dedicated to AI/ML or Generative AI products.
Experience collaborating with enterprise data engineering and cloud infrastructure teams (AWS, Azure, or GCP).

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Keywords to mirror

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