Senior AI Project Manager
Aroha Technologies
Sacramento, CA
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JOB DETAILS
JOB TYPE
Temporary, Contractor, Full-time
SKILLS
Business Analysis, Communication Skills, Credit Risk, Data Analysis, Data Warehousing, Detail Oriented, Establish Priorities, Negotiation Skills, Presentation/Verbal Skills, Problem Solving Skills, Quantitative Analysis, Query Analysis, SQL (Structured Query Language), Scrum Project Management and Software Development, Software Testing, System Integration (SI), Technical Delivery, Writing Skills
LOCATION
Sacramento, CA
POSTED
11 days ago
Senior AI Project Manager
Data & Analytics Division | Enterprise | Full-Time
Department: | Data & Analytics / AI Center of Excellence |
Role Overview
We are seeking a Senior AI Project Manager to lead high-impact, enterprise-scale Data & Analytics initiatives. In this role, you will serve as the connective tissue between data scientists, ML engineers, business stakeholders, and executive leadership — driving AI projects from concept through delivery with rigor, clarity, and strategic intent.
You will be responsible for managing the full project lifecycle of data-intensive AI programmes, ensuring alignment with business objectives, governance standards, and enterprise risk frameworks.
Key Responsibilities
Project Delivery & Governance
• Own end-to-end delivery of enterprise Data & Analytics and AI initiatives, from scoping and planning through execution and post-launch review.
• Define and maintain project charters, roadmaps, risk registers, and stakeholder communication plans.
• Apply structured methodologies (Agile, CRISP-DM, hybrid) appropriate to the complexity of each AI workstream.
• Ensure adherence to enterprise PMO standards, data governance policies, and audit requirements.
Stakeholder & Cross-functional Leadership
• Act as primary liaison between Data Engineering, Data Science, Business Intelligence, and senior business stakeholders.
• Facilitate steering committee updates, executive briefings, and cross-functional working groups.
• Translate complex technical outputs (model performance, data pipeline architecture) into actionable business insights.
Risk, Dependency & Budget Management
• Proactively identify, escalate, and mitigate project risks, dependencies, and blockers across multi-team programmes.
• Manage project budgets, resource allocation, and vendor relationships across analytics tooling and platform contracts.
• Track and report on project KPIs, OKRs, and value realisation metrics.
AI & Data Programme Oversight
• Manage concurrent workstreams across predictive analytics, business intelligence, data platform modernisation, and AI model deployment.
• Partner with Data Architects and ML leads to ensure data readiness, pipeline integrity, and model operationalisation timelines are met.
• Drive adoption of enterprise analytics platforms (e.g., Databricks, Snowflake, Power BI) across business units.
Required Qualifications
• 8+ years of project/programme management experience, with at least 3 years leading Data & Analytics or AI/ML projects in an enterprise environment.
• Proven track record delivering large-scale data transformation programmes (data warehousing, BI modernisation, predictive analytics).
• Strong understanding of the end-to-end analytics lifecycle: data ingestion, transformation, modelling, visualisation, and productionisation.
• Proficiency with project management tools: Jira, Confluence, MS Project, or equivalent enterprise PPM platforms.
• Experience working within enterprise governance and risk frameworks (e.g., data privacy, model risk, GDPR compliance).
• Exceptional stakeholder management skills — ability to operate comfortably from engineering teams to C-suite audiences.
• PMP, PRINCE2, or equivalent project management certification.
Preferred Qualifications
• Familiarity with cloud data platforms: Azure (Synapse, ADF), AWS (Redshift, Glue), or GCP (BigQuery, Dataflow).
• Exposure to MLOps practices and tools (MLflow, Azure ML, SageMaker).
• Experience in regulated industries (financial services, healthcare, manufacturing) with complex data compliance requirements.
• Certification in data-adjacent areas (e.g., Azure Data Fundamentals, Google Data Engineer, Databricks Certified Associate).
• Working knowledge of Python or SQL — sufficient to assess technical feasibility and engage meaningfully with engineering teams.
Core Competencies
Leadership & Influence | Technical Acumen |
• Executive-level communication • Conflict resolution & negotiation • Change management • Strategic thinking | • Data platform literacy • AI/ML lifecycle awareness • Agile & waterfall delivery • Risk & dependency management |
What We Offer
• Competitive senior-level compensation package with performance bonus.
• Opportunity to shape AI and data strategy at enterprise scale.
• Access to cutting-edge cloud and analytics platforms.
• Structured career path toward Director of AI Delivery or Head of Data Programmes.
• Hybrid working model with flexible arrangements.
• Continuous learning budget and professional certification support.
About the Company
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