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Vericast

Senior Project Manager - AI/ML Initiatives (Remote)

Posted 3 Days Ago
Be an Early Applicant
In-Office or Remote
Hiring Remotely in San Antonio, TX
130K-150K Annually
Senior level
In-Office or Remote
Hiring Remotely in San Antonio, TX
130K-150K Annually
Senior level
Lead strategic AI/ML projects, manage multi-disciplinary teams, ensure on-time delivery while promoting ethical AI principles and agile methodologies.
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Company Description

Vericast is the financial institution (FI) performance partner. We help banks and credit unions drive growth, improve efficiency, increase engagement and navigate change through the power of data, technology and people. Our advanced analytics, data-driven insights and integrated solution set enable better execution with agility, precision and scale. That’s why thousands of financial institutions look to Vericast and our 150 years of financial services expertise to help them achieve more. For more information, visit http://www.vericast.com or follow Vericast on LinkedIn.

Job Description

The Senior Project Manager in our Product Management Office (PMO) leads strategic, high-complexity projects and programs focused on artificial intelligence and machine learning initiatives. This role combines technical project leadership with business acumen, managing AI/ML implementations, data platform modernization, intelligent automation, and cross-functional digital transformation efforts. You'll orchestrate projects from concept through production deployment, ensuring AI solutions are delivered on time, within budget, and aligned with business value and ethical AI principles. As a trusted advisor to stakeholders and a mentor to project teams, you'll bridge technical, business, and consulting domains while championing agile methodologies and modern project management practices.

KEY DUTIES/RESPONSIBILITIES

 AI/ML Project Leadership & Delivery: Lead end-to-end delivery of complex AI and machine learning
projects, including model development initiatives, AI platform implementations, intelligent
automation solutions, and generative AI integrations. Drive projects through all lifecycle phases
using hybrid methodologies (Agile, Scrum, Waterfall, MLOps) tailored to AI/ML project needs.
Manage project scope, timeline, budget, and quality standards while navigating the unique
challenges of AI projects (model performance, data requirements, ethical
considerations).Coordinate dependencies across data engineering, ML engineering, data science,
and business stakeholder teams. Navigate the AI project lifecycle from use case identification
through model training, validation, deployment, and monitoring. (25%)

 AI & Intelligent Automation Initiatives: Support implementation and optimization of AI/ML
platforms, including model training infrastructure, MLOps pipelines, feature stores, and model
monitoring systems. Coordinate cross-functional teams on projects involving generative AI
applications, natural language processing, computer vision, predictive analytics, and intelligent
process automation. Partner with data science, engineering, and business teams to deliver AI
solutions that drive measurable business outcomes and ROI. Manage relationships with AI
technology vendors, cloud providers (AWS, Azure, GCP), and AI consulting partners. Ensure
responsible AI practices including bias detection, explainability, data privacy, and governance
frameworks. (20%)

 Stakeholder Communication & Collaboration: Serve as primary point of contact for AI project
teams, business owners, and executive sponsors. Deliver clear, concise communications including
status reports, executive dashboards, and risk assessments tailored for both technical and non-
technical audiences. Translate complex AI concepts and project progress into business value
language for leadership. Facilitate stakeholder alignment through sprint reviews, model review
sessions, steering committee meetings, and AI governance forums. Present project updates, model
performance metrics, and recommendations to leadership using data visualization and storytelling
techniques. (20%)

 Team Coordination & Resource Management: Coordinate distributed, cross-functional teams
including data scientists, ML engineers, data engineers, software developers, UX designers, and
business analysts. Manage daily standups, sprint planning, model review sessions, retrospectives,
and other agile ceremonies. Monitor team velocity, sprint burndown, model development milestones, and progress against OKRs. Request and allocate specialized AI/ML resources based on
skill requirements and project priorities. Navigate resource constraints in competitive AI talent
markets. (15%)

 Change Management & AI Adoption: Partner with business units to ensure smooth
implementation of AI solutions and intelligent automation. Develop and execute change
management plans addressing AI literacy, training, documentation, and user adoption. Validate
that AI capabilities are adopted, monitored, and that governance controls and feedback loops are
established. Review AI deliverables to ensure alignment with acceptance criteria, model
performance benchmarks, and business objectives. Address organizational change resistance and
AI anxiety through education and transparent communication. (10%)

 Mentorship & Knowledge Sharing: Mentor junior and mid-level project managers on
methodologies, tools, and AI project best practices. Stay current on emerging trends in project
management, agile practices, AI technologies, and responsible AI frameworks. Contribute to PMO
process improvements and development of AI-specific templates, frameworks, and lessons
learned. Provide input to performance reviews for project team members. Build organizational AI
literacy through knowledge sharing and documentation. (5%)

 Risk & Change Management: Identify, assess, and mitigate AI-specific project risks including data
quality issues, model performance degradation, ethical concerns, and regulatory compliance.
Evaluate scope changes and their impact on timeline, budget, resources, and model requirements.
Present change requests and recommendations to leadership with supporting analysis and impact
assessments. Maintain RAID logs (Risks, Assumptions, Issues, Dependencies) with AI-specific
considerations and escalate as needed. Monitor and address AI governance, security, and
compliance requirements. (5%)

Qualifications

EDUCATION
 Bachelor's degree in Business, Computer Science, Data Science, Engineering, or related field;
Master's degree or MBA preferred

EXPERIENCE
 5+ years managing large-scale, cross-functional projects and programs in AI/ML, data science,
intelligent automation, or advanced analytics domains
 Proven track record leading multiple systems integration and AI implementation projects through
full lifecycle
 Consulting experience is strongly preferred, with demonstrated ability to quickly adapt to new
business contexts, build stakeholder relationships, deliver value in client-facing or internal
consulting environments, and manage ambiguity in emerging technology spaces
 Hands-on experience with agile frameworks (Scrum, Kanban, SAFe) and traditional methodologies
 Experience supporting AI/ML initiatives such as predictive modeling projects, GenAI
implementations, MLOps platform buildouts, or intelligent automation programs
 Background working with remote and distributed teams across technical and business functions

KNOWLEDGE/SKILLS/ABILITIES
 Understanding of AI/ML concepts including supervised/unsupervised learning, model training and
evaluation, feature engineering, and model deployment
 Familiarity with AI/ML technology stacks, cloud platforms (AWS SageMaker, Azure ML, GCP Vertex
AI), and MLOps tools
 Knowledge of data pipelines, data governance, and data privacy regulations (GDPR, CCPA, AI Act)
as they relate to AI projects
 Awareness of responsible AI principles including fairness, transparency, explainability, and bias
mitigation
 Experience with project management tools (Jira, Asana, Azure DevOps, Monday.com, MS Project)
 Proficiency with collaboration platforms (Confluence, Miro, Slack, Microsoft Teams) and data
visualization tools
 Project Management Excellence: Advanced knowledge of PMI, Agile, and hybrid methodologies
with relevant certifications (PMP, CSM, SAFe, PMI-ACP) preferred
 Strategic Communication: Ability to translate complex AI/ML concepts for business audiences and
business requirements for technical teams
 Influence & Leadership: Proven ability to lead without direct authority and drive consensus across
diverse stakeholders including skeptics of AI technology
 Problem Solving: Strong analytical skills with experience in root cause analysis, risk mitigation, and
creative solution development in uncertain environments
 AI Literacy: Comfort working with emerging AI technologies and ability to learn new AI concepts
quickly
 Continuous Improvement: Knowledge of Lean, Six Sigma, or similar methodologies a plus
 Financial Acumen: Experience with budget management, forecasting, ROI analysis, and business
case development for AI investments
 Consulting Mindset: Structured problem-solving approach, client service orientation, and ability to
deliver actionable insights
 Exceptional organizational abilities with strong attention to detail in fast-paced environments
 Skilled facilitator capable of running productive meetings and gaining buy-in on innovative AI
initiatives
 Diplomatic approach to navigating competing priorities, organizational politics, and technical
trade-offs
 Customer-centric mindset with focus on collaboration, team building, and delivering business value
 Adaptable and comfortable with ambiguity, pivoting strategies, and the iterative nature of AI
development
 Intellectual curiosity and enthusiasm for emerging technologies

Additional Information

Base Salary: $130,000-$150,000

Position is eligible for an annual bonus incentive program.

*Applications will be accepted through December 15, 2025, after which the posting will be closed and no longer available for submissions.*

The ultimate compensation offered for the position will depend upon several factors such as skill level, cost of living, experience, and responsibilities.

Vericast offers a generous total rewards benefits package that includes medical, dental and vision coverage, 401K with company match and generous PTO allowance. A wide variety of additional benefits like life insurance, employee assistance and pet insurance are also available, not to mention smart and friendly coworkers!

At Vericast, we don’t just accept differences - we celebrate them, we support them, and we thrive on them for the benefit of our employees, our clients, and our community. As an Equal Opportunity employer, Vericast considers applicants for all positions without regard to race, color, creed, religion, national origin or ancestry, sex, sexual orientation, gender identity, age, disability, genetic information, veteran status, or any other classifications protected by law. Applicants who have disabilities may request that accommodations be made in order to complete the selection process by contacting our Talent Acquisition team at [email protected]. EEO is the law. To review your rights under Equal Employment Opportunity please visit: www.dol.gov/ofccp/regs/compliance/posters/pdf/eeopost.pdf.

 #LI-KK1 #LI-REMOTE

Top Skills

Agile
AI
Asana
AWS
Azure
Azure Devops
Confluence
Data Science
GCP
JIRA
Kanban
Machine Learning
Microsoft Teams
Miro
Mlops
Ms Project
Scrum
Slack

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