Job Title: Senior AI Project Manager
Work Location: The Woodlands, TX (hybrid)
Duration: 1 year contract with option to extend or hire
Education/Experience Required:
Our company is hiring a Senior AI Project Manager to link its internal innovation group with the rest of the organization. You will take AI initiatives the innovation group has selected for company-wide adoption and manage them through to implementation. The role moves AI work from pilot to production with structured delivery, coordination across functions, and clear communication to leadership.
We're looking for someone who has delivered AI, automation, data, or agentic technology hands-on and knows how to introduce new technology into a large, complex organization. That means working with business owners, technical teams, vendors, security, compliance, and senior leadership.
The position sits within the Project Management Office and is fully assigned to the innovation group's portfolio. The focus is enterprise execution: getting initiatives through every gate, keeping stakeholders aligned, and delivering measurable value at scale.
Job Description & Responsibilities :
- Act as the primary link between the innovation group and the wider organization. Provide the governance, stakeholder alignment, and implementation rigor that take AI initiatives from early testing to full company-wide deployment.
- Partner with innovation leadership on portfolio prioritization and sequencing. Before build begins, confirm each initiative has a business case, baseline metrics, success criteria, and projected ROI. Leadership should always be able to say why an initiative exists, whether it's delivering, and whether it should expand.
- Run the innovation group's eight-stage delivery lifecycle: discovery, prioritization, data and technical readiness, build/proof of concept, evaluation, pilot, production readiness, and launch. Track each initiative against defined entry and exit criteria, required evidence, and executive decision points.
- Standardize delivery methods, templates, governance checkpoints, and reporting discipline so leadership has accurate, reliable visibility into the AI portfolio at all times.
- Remove obstacles by coordinating business, IT, data, enterprise applications, infrastructure, security, legal, and GRC teams. Align on technical feasibility, compliance, security, and operational readiness so initiatives don't stall in the handoff from the innovation group to the business.
- Lead technical evaluations of AI architectures and integration options with engineering, data, and security teams. This covers agentic workflows, LLMs, RAG, APIs, MCP, and automation.
- Manage AI vendor and partner relationships: RFP and SOW support, contract coordination, delivery oversight, budget tracking, and accountability to agreed outcomes.
- Prepare executive communications for the board, steering committees, and leadership. These include briefs, roadmap updates, status reports, decision logs, and implementation recommendations.
- Other duties may be assigned. Responsibilities may change based on business needs.
Skills & Qualifications :
- 7+ years in project and program management, with substantial experience leading enterprise technology, AI, automation, data, digital transformation, or innovation work. Candidates with fewer years but strong hands-on AI delivery experience will be seriously considered.
- Required: practical, hands-on AI experience. Examples include direct work on AI solution delivery, generative AI, machine learning or data-driven products, automation programs, AI pilots, or enterprise AI adoption. Preference goes to people who have built with or directly managed AI delivery teams, not those whose involvement was limited to maintaining a project plan.
- Solid grasp of the full AI delivery lifecycle: use-case discovery, feasibility assessment, data readiness, model or agent design, prompt and workflow iteration, testing, validation, security review, change management, adoption, monitoring, and continuous improvement.
- Experience working with technical AI teams and concepts, including LLMs, AI agents, RAG, APIs, data integrations, automation platforms, model evaluation, responsible AI, data privacy, and enterprise security. You can lead architecture and engineering conversations credibly while leaving those decisions to the technical owners.
- Experience with, or strong working knowledge of, Model Context Protocol (MCP) or comparable integration patterns that securely connect AI applications and agents to enterprise systems, tools, data, workflows, and services under governance.
- Proficiency in delivery and reporting tools such as Azure DevOps, Monday.com, MS Project, Excel, Power BI, Power Platform, collaboration tools, and AI-enabled productivity platforms.
- Proven governance and delivery rigor: roadmap definition, dependency management, RAID management, change control, stakeholder alignment, vendor management, financial tracking, and benefits realization.
- Functional leadership of QA/UAT and release management, including test planning, defect triage, cutover planning, and operational readiness.
- Ability to learn business processes, operational impacts, financial drivers, data flows, and control considerations related to AI-enabled change quickly.
- Strong executive presence and communication skills. You can turn complex AI, data, and technical material into clear business outcomes, implementation plans, risk assessments, and narratives that support decisions.
- High ownership, curiosity, bias for action, close attention to detail, and real enthusiasm for practical uses of emerging technology in the enterprise.
- Nice to have:
- Certifications in PMP, Agile, Scrum, ITIL, AI, AI RMF, AI SDLC, IT Change Management, data, cloud, security, or product management.
- Experience with audit, SOX, cybersecurity, vendor risk, privacy, or responsible AI governance.
