About the job Director of AI & Automation
Director of AI and Automation
Location: San Diego, CA (In-Office) | Type: Full-Time
Role Overview
We are recruiting on behalf of a growing AI consulting and implementation firm based in San Diego. This is a foundational leadership hire reporting directly to the President. The Director of AI and Automation will own the internal AI strategy, data infrastructure, and team build from scratch, creating the systems and capabilities that underpin how the business delivers results for its clients.
This is a player-coach role. The right candidate sets strategy and owns architecture decisions while staying close enough to the work to design the right solutions, catch problems early, and execute when needed. Someone who can only manage and someone who can only build are both the wrong fit.
Key Responsibilities
AI Strategy, Infrastructure and Deployment
- Own the AI and data strategy across the business, covering governance, architecture, accessibility, and deployment
- Assess and remediate current data infrastructure, including CRM data, inventory systems, and financial reporting
- Architect and oversee cloud-native data warehouse solutions with a focus on scalability, cost efficiency, and cross-location accessibility (Snowflake strongly preferred; BigQuery or Redshift also valued)
- Design and oversee modern ELT/ETL pipelines using dbt, Airflow, Fivetran, and Python-based frameworks
- Define and enforce data governance standards including ownership, quality controls, lineage tracking, and access management
- Lead customer-facing AI implementation across CRM, sales, and service including lead scoring, follow-up automation, and AI-assisted workflows
- Evaluate existing AI tools for proper implementation and redundancy; many tools are already in place and need to be made to actually work
- Identify and execute AI and automation initiatives with clear ROI tied to operational efficiency, customer retention, and revenue performance
- Evaluate and manage vendor and technology partner relationships across the AI and data stack
Stakeholder Leadership
- Serve as the primary AI advisor to the executive team, translating technical strategy into clear business decisions
- Partner with department leads to understand real operational pain points and design solutions that work in practice
- Run executive-level reporting and strategy sessions with clarity and confidence
- Drive change management and adoption; accountable for whether people actually use what gets built, not just whether it was built
Team Building
- Build and lead a lean, high-performing AI team; execute without needing to build a large department first
- Define what to build internally, what to hire for in Latin America, and where to rely on external partners
- Work alongside the existing BI team to strengthen capability and establish a clear path for the data organization
- Manage team performance, provide coaching and mentorship, and build a culture of accountability
Requirements
Essential
- 8 to 12 or more years in data engineering, data architecture, or a closely related technical role, with at least 3 to 5 years in senior leadership with cross-functional accountability
- Strong hands-on data infrastructure and cleanup experience; you have fixed broken data environments and established governance where data quality was a real problem, not just a future aspiration
- Hands-on experience with modern data stack: Snowflake (strongly preferred), dbt, Fivetran, Airflow, BI tools (Tableau, Power BI, or Looker), and cloud platforms (AWS, Azure, or GCP)
- Deep proficiency in SQL and Python with production pipeline and transformation experience
- Practical experience deploying AI and ML solutions in production; real systems used by real people, not proofs of concept
- Retail, CRM, or customer-facing implementation experience in consumer-facing businesses where lead management and customer lifecycle tools are central to operations
- Equally comfortable architecting a data warehouse and presenting a strategy roadmap to executive leadership
- Experience hiring and managing technical teams including distributed or offshore resources
- Comfortable creating structure where none exists and moving without a perfectly defined mandate
Desirable
- Spanish language proficiency; this role includes building and leading engineering and analytics resources in Latin America and candidates with this experience will receive priority consideration
- Experience with Snowflake Cortex, Snowpark, Databricks, or BigQuery
- Background as a founder or early-stage data leader who has owned the full problem before building a team
Competitve Compensation