- Company Name
- First West Credit Union
- Job Title
- Director, AI Technology
- Job Description
-
**Job Title**
Director, AI Technology
**Role Summary**
Lead the end‑to‑end design, development, and operational delivery of advanced AI capabilities across the enterprise. Set AI strategy, architecture, and best‑practice standards, mentor cross‑functional engineering teams, and align technology initiatives with business objectives while ensuring scalability, safety, compliance, and risk controls.
**Expectations**
- Own the vision and roadmap for AI technology in the organization.
- Deliver measurable business value through production AI systems.
- Foster a culture of engineering excellence and continuous learning.
- Maintain rigorous risk, compliance, and security standards.
**Key Responsibilities**
- Define reference AI architecture, including multi‑agent orchestration, RAG pipelines, tool interfaces, and policy enforcement layers.
- Provide technical leadership: run design reviews, mentor engineers, establish reusable libraries and standards.
- Translate business opportunities into prioritized, executable AI solutions, coordinating with Data, Cloud, Security, and Application teams.
- Participate hands‑on engineering: build complex components, perform performance tuning, observability, and incident response.
- Lead the build, implementation, and optimization of AI ecosystems; define consumption, usage, and access processes.
- Collaborate with stakeholders to ensure solutions meet desired outcomes and deliver measurable value.
- Monitor industry trends, evaluate platform and vendor capabilities, and recommend upgrades or deprecations.
- Ensure compliance with audit, risk, and regulatory requirements (e.g., OSFI, FCAC).
**Required Skills**
- 8+ years in software or AI engineering with 3–5 years in technical leadership.
- Proven experience designing and deploying production AI systems in enterprise/financial services environments.
- Strong strategic thinking, planning, and project management.
- Excellent communication, mentoring, and relationship‑building abilities.
- Deep understanding of AI engineering patterns: retrieval‑augmented generation, agentic workflows, prompt engineering, secure model integration.
- Proficiency in cloud architecture, identity/security best practices, and application observability.
- Ability to balance theory and hands‑on implementation, driving technical ownership and risk management.
**Required Education & Certifications**
- Bachelor’s degree in Computer Science, Engineering, or related field (Master’s preferred).
- Relevant certifications in AI/ML, cloud architecture, or security may be an asset but are not mandatory.