Senior PM — AI Personalization Platform

Kelly Services

Irving (TX)

On-site

USD 77,000 - 84,000

Full time

11 days ago

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Job summary

Kelly Services is seeking a Senior Project Manager for an AI & Personalization Platform on a 12+ month fully onsite contract in Irving, TX. The role requires a PMP certification and 7+ years delivering technical and AI-related initiatives.

You will lead cross-functional teams across product, data, and engineering to implement platform capabilities with strong executive communication. The ideal candidate will manage APIs, data pipelines, and model services while driving governance, risk, and

Qualifications

PMP certification is required.
7+ years of PM experience delivering technical/software/data initiatives.
Hands-on leadership of cross-functional teams across product, engineering, data, architecture and operations.

Responsibilities

Own end-to-end delivery of AI and Personalization Platform initiatives, including problem definition, scope, integrated plans, schedules, risks, dependencies, stakeholder communication, launch readiness, and post-launch measurement.
Build and maintain an integrated platform roadmap with foundational capabilities, product increments, enablers, and enterprise dependencies.
Translate platform strategy and prioritized opportunities into milestone-based delivery plans with clear owners and timelines.
Establish and run an intake/prioritization process for AI/personalization requests balancing value, data readiness, feasibility, capacity, cost and risk.
Coordinate delivery across product, AI/ML engineering, software engineering, data engineering, data science, architecture, platform ops, QA, privacy, security, legal, and vendor teams.
Drive the AI/personalization delivery lifecycle from discovery through deployment, monitoring and improvement.
Coordinate platform capabilities such as data pipelines, feature/profile services, model services, decisioning, APIs, integrations, observability and tooling.
Partner with leaders to define acceptance criteria and evaluation plans covering relevance, accuracy, latency, scalability, safety and business outcomes.
Establish launch-readiness practices for platform releases including validation, performance testing, integration testing and rollback planning.
Coordinate monitoring and continuous-improvement plans for production AI/personalization capabilities, including model drift and data quality.
Establish governance for AI/personalization delivery including privacy, responsible-AI controls, data lineage, documentation and auditability.
Run Agile delivery cadences within a product/engineering operating model.
Proactively manage RAID; remove blockers and elevate early with options and trade-offs.
Coordinate build-versus-buy evaluations and vendor/SOW workstreams for AI platforms and related tooling.
Track staffing, budget, platform consumption and vendor spend against plan.