AI Director

Overview

Gilbane is seeking a seasoned and forward-thinking AI Director with a strong foundation in IT, proven experience in data and AI, and a passion for turning innovation into enterprise impact. In this leadership role, you will guide a small team of AI Solutions Analysts and act as the key architect and delivery owner for AI solutions that connect advanced capabilities with real-world business value.

This role will report to the Chief Growth and Strategy officer.

You will work closely with business leaders and functional teams to identify and prioritize high‑value AI opportunities, ensuring that solutions are technically sound, scalable, and aligned with strategic priorities. Beyond model development, you will lead the integration of AI into existing systems, oversee end‑to‑end deployment, and establish the engineering standards, governance, and best practices needed to scale AI responsibly and efficiently across the enterprise.

This position is ideal for someone who thrives at the intersection of technology, product, and leadership—a hands‑on director and team builder who can bridge vision and execution. You will play a pivotal role in shaping the enterprise AI ecosystem, transforming ideas into robust, production‑ready solutions that accelerate growth, efficiency, and competitive advantage.

• Lead, mentor, and develop a team of AI Solutions Analysts; set goals, review performance, and grow skills.
• Allocate work, remove blockers, and establish delivery rituals (stand‑ups, code reviews, demos, retros).
• Model engineering best practices, documentation standards, and a culture of reliability and accountability.
• Develop and lead Gilbane AI strategy in alignment with business goals and digital transformation initiatives.
• Design, develop and deploy high‑impact AI solutions (GenAI and traditional ML) that enhance project delivery, safety, operational efficiency, workforce enablement, client enablement and unlock new value.
• Own full lifecycle: discovery, prototyping, testing, hardening, deployment, and post‑launch iteration.
• Ensure integration with existing systems and workflows.
• Document technical designs, processes, and outcomes for knowledge sharing and scalability and provide training, and support to drive AI adoption across teams.
• Evaluate and recommend AI tools, platforms, and technologies (buy vs build).
• Monitor performance to ensure high‑quality, scalable solutions.
• Stay updated on emerging AI trends and technologies, risks and opportunities to ensure the organization remains competitive.
• Partner with business owners to frame problems, define success metrics, and prioritize a clear backlog. Collaborate with the IT team and other support functions.
• Translate business requirements into engineering tasks and acceptance criteria; communicate status and risks proactively.
• Prepare and deliver executive‑ready updates and demonstrations.
• Work with IT and data teams to source, prepare, and govern high‑quality data.
• Design feature pipelines and governance strategies.
• Embed Responsible AI controls (privacy, security, bias testing, explainability) into each lifecycle stage and ensure AI solutions adhere to ethical guidelines, data privacy regulations, and Responsible AI principles. Address potential biases in AI models and ensure transparency.
• Produce and maintain model/solution documentation (model cards, data lineage, evaluation results, user guidance).
• Manage relationships with external AI vendor, consultants, and technology providers.
• Coordinate with Legal/Compliance on data use and third‑party tools.
• Create user training, quick‑start guides; measure adoption and satisfaction.
• Gather feedback, prioritize enhancements, and drive continuous improvement.
• Define and track KPIs (e.g., cycle‑time reduction, accuracy/quality uplift, cost‑to‑serve, user adoption) to measure success of AI solutions (ROI).
• Report outcomes and lessons learned; continuously monitor and optimize AI models and systems and capture reusable components (prompts, evaluators, connectors) in a shared library.

• 8+ years of experience in AI or related field.
• Expertise in AI / ML, deep learning, NLP, predictive analytics and modern…