Senior Project Manager - AI & Personalization Platform

Motion Recruitment

Irving (TX)

On-site

USD 120,000 - 180,000

Full time

37 hours ago
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Job summary

Motion Recruitment is seeking a Senior Project Manager - AI & Personalization Platform for a 12+ month on-site contract in Irving, TX. You will own end-to-end delivery of AI and personalization initiatives, coordinating across product, data, engineering, architecture, and operations to ensure successful outcomes.

The role requires PMP, 7+ years in project or program management, and strong executive communication.

Qualifications

  • PMP certification from PMI required.
  • 7+ years of project or program management delivering technical/software/data/platform initiatives.
  • Experience leading cross-functional delivery across product, engineering, data, architecture, operations, and business teams.
  • Experience delivering AI/ML, personalization, or platform initiatives; direct model development not required.
  • Strong governance of AI/personalization risk, privacy, security, bias, explainability, and data governance.

Responsibilities

  • Own end-to-end delivery of AI and Personalization Platform initiatives, including scope, plans, risks, dependencies, and post-launch measurement.
  • Build and maintain an integrated platform roadmap with foundational capabilities and enterprise dependencies.
  • Translate strategy and opportunities into milestone delivery plans with clear owners and timelines.
  • Establish intake and prioritization processes for AI/personalization platform requests.
  • Coordinate delivery across product, AI/ML engineering, data science, architecture, operations, and vendors.
  • Run Agile delivery cadences and manage RAID items; resolve blockers and escalate trade-offs.
  • Track staffing, budget, and vendor spend against plan.

Skills

PMP certification
Cross-functional leadership
Executive communication
Stakeholder management
Vendor management
Risk management

Education

Bachelor's degree or equivalent

Tools

Jira
Confluence
Smartsheet
MS Project

Job description

Our client is seeking a Senior Project Manager - AI & Personalization Platform for a 12+ month fully onsite contract in Irving, TX!

No C2C!

Required Skills & Experience
  • PMP certification from the Project Management Institute required.
  • 7+ years of project or program management experience delivering technical, software, data, platform, AI/ML, or digital initiatives.
  • Demonstrated experience leading cross-functional delivery across product, engineering, data, architecture, operations, and business teams on concurrent, interdependent initiatives.
  • Experience delivering or operating AI/ML, personalization, recommendation, decisioning, experimentation, or advanced analytics platforms; direct model development is not required.
  • Working knowledge of the AI/ML and platform delivery lifecycle, including data readiness, solution development, evaluation, deployment, observability, monitoring, iteration, and retirement.
  • Practical understanding of AI and personalization risks and controls, including privacy, security, bias and fairness, explainability, human oversight, data governance, and model or solution performance.
  • Experience managing platform initiatives with APIs, integrations, services, data pipelines, cloud infrastructure, reliability requirements, or operational support models.
  • Hands‑on experience with Agile/Scrum delivery as well as hybrid and waterfall approaches, and with delivery tooling such as Jira, Confluence, Smartsheet, or MS Project.
  • Proven track record of dependency, risk, issue, vendor, and stakeholder management on complex, multi‑team programs.
  • Strong executive communication and status‑reporting skills, with the ability to make AI concepts, platform dependencies, uncertainty, and trade‑offs clear to both technical and business audiences.
  • Bachelor’s degree or equivalent practical experience.
Desired Skills & Experience
  • Experience with generative AI, large language models, retrieval‑augmented generation, AI agents, prompt evaluation, content generation, or conversational AI platforms.
  • Experience delivering recommendation systems, next‑best‑action, ranking, propensity, customer segmentation, profile, decisioning, or real‑time personalization capabilities.
  • Familiarity with MLOps, model monitoring, feature stores, data quality, experimentation platforms, model registries, evaluation frameworks, or feature and decisioning services.
  • Familiarity with cloud‑native platforms, APIs, event‑driven architectures, streaming data, microservices, observability, platform reliability, and infrastructure‑as‑code.
  • Experience establishing responsible‑AI governance, model‑risk processes, privacy reviews, security reviews, or enterprise AI standards.
  • Experience managing platform modernization, technical‑debt reduction, scalability improvements, performance optimization, or reliability programs.
  • Additional certifications such as PMI‑ACP, CSM/PSM, SAFe, or an AI/ML, product, cloud, or data certification.
  • Experience managing build‑versus‑buy evaluations and vendor‑delivered AI, personalization, data, or platform workstreams.
  • Retail, convenience‑retail, loyalty, consumer technology, or customer‑experience platform experience.
What You Will Be Doing
  • 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, sequencing foundational capabilities, product increments, technical enablers, and enterprise dependencies.
  • Translate platform strategy, business needs, technical assessments, and prioritized opportunities into milestone‑based delivery plans with clear owners, timelines, dependencies, and success criteria.
  • Establish and run a clear intake and prioritization process for AI and personalization platform requests, balancing strategic value, customer impact, data readiness, technical feasibility, capacity, cost, and risk.
  • Coordinate delivery across product, AI/ML engineering, software engineering, data engineering, data science, architecture, platform operations, QA, privacy, security, legal, and vendor teams.
  • Drive the AI and personalization delivery lifecycle from discovery and data readiness through solution design, development, evaluation, testing, deployment, monitoring, and continuous improvement.
  • Coordinate platform capabilities such as data pipelines, feature and profile services, model services, decisioning, recommendation and ranking, experimentation, APIs, integrations, observability, and operational tooling.
  • Partner with product and technical leaders to define acceptance criteria and evaluation plans covering relevance, accuracy, quality, latency, scalability, reliability, safety, fairness, explainability, cost, adoption, and business outcomes as appropriate.
  • Establish launch‑readiness practices for platform releases, including technical validation, performance testing, integration testing, operational readiness, documentation, support ownership, and rollback planning.
  • Coordinate monitoring and continuous‑improvement plans for production AI and personalization capabilities, including model drift, data quality, performance degradation, service health, unexpected behavior, and changing business conditions.
  • Establish practical governance for AI and personalization delivery, including privacy, security, responsible‑AI controls, data lineage, model or solution documentation, human oversight, approval checkpoints, and auditability.
  • Run Agile delivery cadences within a product and engineering operating model, including planning, backlog refinement, standups, reviews, retrospectives, roadmap reviews, and release checkpoints.
  • Proactively manage risks, issues, assumptions, dependencies, and decisions (RAID); remove blockers and elevate early with recommended options and trade‑offs.
  • Coordinate build‑versus‑buy evaluations and vendor/SOW workstreams for AI platforms, personalization services, data products, experimentation tools, and supporting technologies.
  • Track staffing, including FTE and contractor capacity, budget, platform consumption, vendor spend, and resourcing against plan.

Posted By: Jamie Prater

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