Technical Program Manager

Role Overview

• Own end-to-end program governance — establishing the PMO structure, governance forums, and reporting cadences.
• Define and manage the integrated program plan across all AI workstreams (Generative AI, Data Science, GCP infrastructure, integrations), tracking milestones, dependencies, and critical path.
• Run project planning, reviews, and RAG with technical leads; maintain velocity metrics and remove blockers.
• Ensure all deliverables are tracked against scope, schedule, budget, and quality criteria, with proactive escalation of deviations.
• Maintain program documentation — charter, WBS, RACI, status reports, and decision logs — to the highest standards.
• Own the program RAID log.
• Proactively identify, assess, and prioritize risks across all workstreams with clear ownership and mitigation plans.
• Design and enforce the change control process — evaluating scope changes for impact on timeline, budget, and resources before presenting recommendations to the steering committee.
• Establish escalation pathways and manage critical issues to resolution.
• Conduct regular risk workshops to embed a risk-aware culture within the delivery team.
• Serve as the primary point of contact for client program stakeholders — building trusted relationships with business sponsors, technology executives, and operational teams.
• Prepare and present executive-level status reports, steering committee packs, and milestone reviews to senior leadership.
• Facilitate alignment between client's internal teams and the delivery organization, managing expectations and resolving conflicts.
• Own resource planning across the program — forecasting demand, managing onboarding/offboarding, and ensuring the right skills are available across all workstreams.
• Track utilization, manage bench transitions, and coordinate with HR and recruitment for timely fulfillment of open roles.
• Foster a high-performance, distributed team culture — supporting well-being, recognizing contributions, and maintaining morale.
• Own the program budget — tracking actuals against forecast, managing contingency, and producing monthly financial reports for internal and client governance.
• Identify and escalate budget risks early; implement corrective actions to maintain P&L health.
• Support commercial activities including SOW management, change order negotiations, invoice tracking, and contract renewals.
• Contribute effort estimates, resource plans, and delivery timelines to presales and solutioning for new workstreams or extensions.
• Maintain working knowledge of the GCP and Google AI stack — including Vertex AI, BigQuery, and associated data and ML services — to effectively govern delivery across infrastructure, model development, and integration workstreams.
• Understand the unique delivery dynamics of agentic AI programs — including multi-agent orchestration, tool-use design, prompt engineering cycles, and the governance considerations around autonomous decision-making systems.
• Oversee delivery of intelligent automation and RPA workstreams — understanding bot lifecycle management, exception handling frameworks, orchestration platforms, and the interplay between RPA, AI, and enterprise systems.
• Adapt PM practices to the non-linear, iterative nature of ML and AI delivery — managing experimentation phases, data dependency risks, model validation cycles, and the transition from prototype to production.
• Act as a translator and bridge between business stakeholders who think in outcomes and technical teams who think in architectures — facilitating shared understanding and aligned decision-making across both worlds.
• Establish and track program KPIs and OKRs;
• Produce regular insights on delivery health, team performance, and program ROI.
• Lead retrospectives and implement lessons learned to build a culture of continuous improvement.
• Contribute to internal PM frameworks, playbooks, and templates for AI program delivery — creating reusable assets for future engagements.
• Represent the organization in client QBRs, program audits, and governance reviews, maintaining the program's compliance posture at all times.

Requirements

• Bachelor's or Master's degree in Engineering, Computer Science, Business Administration, or a related field.
• 10+ years of project/program management experience with at least 5 years managing large-scale digital transformation, cloud, or AI/ML programs.
• Demonstrated experience managing enterprise client engagements in a consulting or system integrator environment — ideally at a global technology firm.
• Strong understanding of AI/ML delivery lifecycle — including data preparation, model development, MLOps, and LLM integration — sufficient to manage technical teams and client expectations effectively.
• Proven track record of managing cross-functional teams of 15+ people across multiple concurrent workstreams.
• Hands-on experience with Agile, Scrum, and SAFe delivery frameworks; comfortable operating in hybrid Agile-Waterfall environments.
• Experience with program financials — budget ownership, P&L tracking, and commercial/contract management.
• PMP, PRINCE2, PgMP, or equivalent program management certification is strongly preferred; Agile certifications (SAFe SP, CSM) are a plus.
• Exceptional communication and executive presentation skills — able to adapt style for engineering teams, business sponsors, and C-suite audiences.
• Proficiency with delivery tooling: JIRA, Confluence, MS Project, Smartsheet, Google Workspace; familiarity with reporting tools (Looker, PowerBI) preferred.

Tech Stack

• BigQuery
• Cloud
• Google Cloud Platform
• PMP
• RPA

Benefits

• 100% payroll + benefits by law
• Work from home (Anywhere in México)
• 30-day Christmas bonus
• 16 vacation days
• 1 economic day a year
• Grocery coupons
• Savings fund
• Home office stipend
• Major medical insurance
• Life insurance
• Training & certifications