Senior Business Analyst, AI

wk

Dallas (TX)

On-site

USD 90,000 - 150,000

Full time

3 days ago
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Job summary

wk is seeking an AI / Agentic Product Owner to own the post-release lifecycle of agentic AI products in a fast-paced environment.

You will manage backlogs, prioritize work across engineering, AI enablement, and business stakeholders, and translate feedback into actionable improvements. The role emphasizes collaboration, scalability, and delivering business value from AI solutions.

Qualifications

  • Bachelor's degree or equivalent experience required.
  • Experience in Agile environments and cross-functional collaboration.
  • Experience with AI/ML-enabled products or intelligent automation is preferred.

Responsibilities

  • Own and manage the post-release product backlog for agentic AI solutions.
  • Coordinate with engineering, QA, AI Enablement, and stakeholders to plan releases.
  • Translate feedback and performance signals into prioritized backlog items.
  • Lead cross-functional backlog trade-offs balancing urgency, business value and user impact.
  • Own product decisions post-launch and ensure alignment with business value and roadmap.
  • Help scale practices for managing multiple live AI products.

Skills

Strong prioritization
Agile practices
Cross-functional coordination
AI/ML-enabled products

Education

Bachelor's Degree or equivalent experience
MBA or advanced degree

Job description

BASIC FUNCTION

The AI / Agentic Product Owner is responsible for post-release ownership and continuous optimization of agentic AI products. This role ensures that deployed AI solutions deliver ongoing business value through effective backlog management, prioritization, and cross-functional coordination. The Agentic Product Owner serves as the primary decision-maker for live AI products, translating feedback, performance signals, and business needs into prioritized work. This role partners closely with AI Enablement, AI Trainers, engineering, and business stakeholders to continuously refine agent behavior, improve outcomes, and scale AI capabilities. This role also requires a foundational understanding of generative AI concepts (e.g., LLMs, RAG, prompt behavior) to effectively manage AI-driven backlogs and product decisions.

ESSENTIAL DUTIES AND RESPONSIBILITIES
Own Post-Release Product Lifecycle
  • Own and manage the post-release product backlog for agentic AI solutions
  • Continuously evaluate product performance and identify improvement opportunities
  • Ensure AI products evolve in alignment with business objectives and user needs
  • Drive ongoing optimization of AI capabilities after launch
Backlog Management and Prioritization
  • Intake and triage feedback, bugs, and enhancement requests from stakeholders
  • Define, prioritize, and maintain a clear, actionable backlog
  • Balance competing priorities across defect resolution, AI performance improvements, and new features
  • Lead release planning and prioritization decisions for live AI products
  • Translate post-release feedback, usage patterns, defect trends, and business needs into prioritized backlog items
  • Make backlog trade-off decisions across multiple live agentic AI products, balancing urgency, business value, user impact, and delivery capacity
Cross-Functional Coordination
  • Act as the central point of coordination across business stakeholders, engineering and QA teams, AI Enablement, and AI Trainers
  • Translate post-release feedback, business needs, and operational improvement opportunities into clear product requirements, user stories, and acceptance criteria
  • Ensure alignment on priorities, timelines, and expected outcomes
  • Coordinate with business SMEs, content owners, AI Enablement, AI Trainers, engineering, and QA to ensure backlog items are well understood and actionable
  • Facilitate prioritization discussions where feedback, defects, content gaps, AI behavior concerns, and enhancement requests compete for delivery capacity
AI Performance and Feedback Integration
  • Collaborate with AI Trainers and AI Enablement to incorporate AI behavior analysis and performance insights into backlog decisions
  • Incorporate feedback into backlog prioritization
  • Ensure improvements are driven by user feedback, usage patterns, and quality issues
  • Leverage AI Trainer and AI Enablement expertise for analysis of agent behavior, prompt sensitivity, grounding issues, response quality, and improvement opportunities
  • Ensure AI-related issues are appropriately categorized, such as product defect, content gap, prompt/behavior issue, user experience gap, or training/adoption need
Product Decision Ownership
  • Serve as the primary decision-maker for product direction, prioritization, and trade-offs
  • Ensure clear ownership of product outcomes post-launch
  • Own decisions regarding what gets fixed, enhanced, deferred, or escalated for live AI products
  • Partner with business sponsors and stakeholders to ensure post-release product decisions remain aligned to business value, user impact, and roadmap priorities
Support Scalable Operating Model
  • Enable a distributed ownership model with clear backlog accountability per AI product
  • Contribute to scalable practices for managing multiple concurrent AI products
  • Effectively manage a portfolio of multiple live agentic AI products (typically 2-4 concurrently), balancing priorities across them
  • Help mature repeatable practices for intake, triage, prioritization, release planning, product health reviews, and transition to steady-state support
JOB QUALIFICATIONS
Education
  • Bachelor's Degree or equivalent experience
Preferred:
  • Business, Technology, or related field
  • MBA or advanced degree
Experience
  • 7+ years in Product Ownership, Business Analysis, or related roles
  • Experience working in Agile environments
  • Experience coordinating across business, technology, QA, and operational stakeholders
Preferred Experience
  • Experience working with AI/ML-enabled products or intelligent automation
  • Familiarity with AI behavior evaluation, prompt iteration, or model output analysis
  • Foundational understanding of generative AI concepts such as LLMs, retrieval-augmented generation (RAG), and prompt-driven workflows
  • Experience in platform, SaaS, or enterprise product environments
  • Experience translating user feedback, performance data, or support trends into actionable product improvements
Key Skills
  • Strong prioritization a
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