Project Manager

Precision Technologies; Irving (TX); On-site; USD 120,000 - 160,000; Part time

Job summary

Precision Technologies seeks a Senior Project Manager for the AI & Personalization Platform based in Irving, TX. This contract role leads end-to-end delivery across platform foundations, data capabilities, model services, APIs, and governance.

You will translate strategy into actionable delivery plans, manage intake, and coordinate cross-functional teams to ensure scalable, measurable enterprise-ready AI capabilities.

Qualifications

• Bachelor's degree or equivalent practical experience.
• PMP certification required.
• 7+ years of project or program management experience delivering technical, software, data, or platform initiatives.
• Experience leading cross-functional delivery across product, engineering, data, architecture, operations, and business teams.
• Experience with AI/ML, personalization, or platform delivery lifecycle.

Responsibilities

• Own end-to-end delivery for AI and personalization platform initiatives, including scope, plans, risks, dependencies, and launch readiness.
• Build and maintain an integrated platform roadmap aligning foundational capabilities with enterprise needs.
• Translate strategy into milestone-based plans with clear owners, timelines, and success criteria.
• Establish intake and prioritization for platform requests, balancing value, feasibility, and risk.
• Coordinate delivery across product, AI/ML, software, data, architecture, operations, privacy, security, legal, and vendor teams.
• Drive the delivery lifecycle from discovery through deployment, monitoring, and continuous improvement.
• Establish governance for privacy, security, responsible AI, data lineage, and auditability.

Skills

PMP certification

Agile/Scrum

Executive communication

Cross-functional leadership

Stakeholder management

AI/ML platform delivery

Cloud platforms

Education

Bachelor’s degree or equivalent

Tools

Jira

Confluence

Smartsheet

MS Project

Job description

Role: Senior Project Manager – AI & Personalization Platform (13620 )

Location: Irving, TX

Duration: Contract

About the job:

You will join a multidisciplinary AI and personalization platform organization spanning product management, AI/ML engineering, software engineering, data engineering, data science, architecture, platform operations, quality assurance, privacy, security, and external partners.

As Senior Project Manager, you will own end-to-end delivery for the AI and Personalization Platform roadmap. You will coordinate initiatives across platform foundations, data and feature capabilities, model and decisioning services, personalization services, experimentation, APIs, integrations, observability, and governance.

You will translate platform strategy into actionable delivery plans, establish clear intake and prioritization, manage dependencies across technical teams, and keep leadership informed through concise, decision-ready reporting. You will help the organization deliver AI and personalization capabilities that are scalable, reliable, measurable, responsible, and ready for enterprise adoption.

Key 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, 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.
• 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.
• Experience with generative AI, large language models, retrieval-augmented generation, AI agents, prompt evaluation, content generation, or conversational AI platforms.
• 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 success looks like

• The AI and Personalization Platform roadmap is prioritized, transparent, and connected to measurable customer, platform, and business outcomes.
• Platform initiatives move predictably from intake through production launch with clear ownership, evaluation criteria, governance, and decision points.
• Core platform capabilities are scalable, reliable, observable, secure, and ready for adoption by downstream product and engineering teams.
• Production AI and personalization services are monitored and improved using agreed quality, relevance, adoption, operational, and financial measures.
• Stakeholders have a shared view of delivery status, risks, dependencies, capacity, platform costs, and expected value.
• Teams use repeatable delivery and governance practices that enable responsible innovation without compromising privacy, security, reliability, or customer trust.