Role Summary
Automation and AI Lead responsible for shaping and executing the organization's overarching artificial intelligence and intelligent automation strategy. In this role, you will champion the transition from traditional workflows to an AI-first operating model, positioning the company at the forefront of technological innovation.
You will be providing leadership to engineers, data analysts, and cross-functional teams. You will align AI/ML investments with macro business goals, establish robust corporate governance for ethical AI, manage vendor relationships, and own the total value realization (ROI) of our intelligent automation portfolio.
Qualifications and Experience
- Master's or Bachelor's degree in Computer Science, Artificial Intelligence, Data Science, Engineering, or a heavily quantitative field.
- Minimum of 12+ years of professional experience in software engineering, enterprise architecture, machine learning, or advanced data analytics.
- 5+ years of senior managerial experience, with a proven track record of leading multi-tiered teams (managing managers) and scaling engineering departments.
- Demonstrated experience in driving large-scale digital transformations or launching enterprise-grade AI products to market that yielded substantial business growth.
Certifications (Preferred)
- Leadership & Management: High-level leadership certifications from accredited institutions (e.g., Executive Leadership Programs, PMP).
- AI & Governance: Certified Artificial Intelligence Governance Professional (IAPP AIGP) or specific enterprise governance certifications (e.g., CGEIT).
- Cloud Executive: Cloud Digital Leader or specialized Executive Cloud Architecture credentials from AWS, Google Cloud, or Microsoft.
Key Responsibilities:
Departmental Leadership& Organizational Design
- Provide strategic direction, mentorship, and leadership to engineering managers, principal architects, and data scientists across the Automation and AI division.
- Establish a high-performance engineering culture rooted in continuous innovation, operational excellence, and responsible experimentation.
- Oversee talent acquisition, global resource allocation, succession planning, and performance management for the department.
Enterprise AI Strategy & Technology Roadmap
- Define and execute the long-term enterprise vision and roadmap for Generative AI (LLMs), predictive analytics, Machine Learning, and Intelligent Process Automation.
- Evaluate emerging AI/ML technologies, frameworks, and market trends to ensure the organization maintains a competitive advantage.
- Drive architectural standardization and platform selection across the global organization to eliminate technical silos and redundancy.
Financial Management & ROI Accountability
- Formulate and manage the annual operational and capital expenditures (OpEx/CapEx) budget for the Automation and AI department.
- Define corporate KPIs and business metrics to measure, track, and report on the financial impact, efficiency gains, and cost reductions driven by AI initiatives.
AI Governance, Risk Management & Compliance
- Establish and chair the organization's Responsible AI & Ethical Governance Board, defining policies for model bias mitigation, data privacy, and explain ability.
- Ensure all automated systems and AI applications strictly adhere to evolving international standards and legal frameworks (e.g., EU AI Act, SOC 2, ISO 42001, GDPR).
- Collaborate with the Chief Information Security Officer (CISO) and Legal counsel to mitigate intellectual property risks, data leakage, and security vulnerabilities associated with Generative AI.
Corporate Stakeholder Management & Evangelism
- Serve as the primary executive sponsor and evangelist for AI and Automation across the enterprise, influencing peers and business leaders to adopt automated solutions.
- Partner with Executive Vice Presidents and business unit heads (Product, Operations, Risk, Finance) to identify high-value strategic automation initiatives.
- Translate complex mathematical, data science, and infrastructural paradigms into clear, executive level business outcomes and growth strategies.
Vendor Management & Strategic Partnerships
- Lead negotiations, contractual evaluations, and service level agreements (SLAs) with global technology vendors, cloud providers, and specialized AI consultancies.
- Establish strategic relationships with leading AI research institutions, technology hyperscale's, and open-source communities to drive collaborative innovation.
- Orchestrate a balanced Build vs. Buy framework for enterprise tools, ensuring optimal utilization of internal engineering resources.
