AI Engineer

Role overview

AI assessment and solution design

• Assess business problems and AI opportunities, determine whether AI is appropriate, and define use cases, requirements, success measures, scope, and implementation plans.
• Define and review solution architecture, technical and data requirements, integrations, infrastructure, APIs, security, and dependencies.
• Assess technical feasibility, data readiness, infrastructure, risks, constraints, and technical dependencies.

Development, evaluation, and delivery

• Develop, configure, integrate, or support implementation of machine learning, generative AI, large language models, and AI agents.
• Define testing and evaluation frameworks, benchmarks, and acceptance thresholds for model and solution quality, performance, reliability, security, safety, and bias.
• Support proofs of concept and pilots, including setup, testing, performance measurement, issue resolution, documentation, and recommendations.
• Evaluate vendors and proposals, challenge technical assumptions, support build-versus-buy decisions, and identify risks and dependencies.
• Support production deployment, integration, documentation, monitoring, support models, and handover.
• Establish performance monitoring and indicators; support optimization, retraining, evaluation, and lifecycle management.

Governance and project support

• Track technical milestones, dependencies, risks, issues, decisions, and deliverables across AI initiatives and help resolve implementation barriers.
• Embed technical requirements for AI governance, privacy, cybersecurity, responsible AI, regulatory compliance, human oversight, traceability, and risk management throughout the lifecycle.

Qualifications and capabilities

• Expertise in artificial intelligence, machine learning, data science, or a related discipline.
• The role calls for hands-on AI expertise, strong technical judgment, and project lifecycle competency.
• Ability to collaborate across business, technology, cybersecurity, data, vendor, and partner teams.
• Ability to deliver solutions that are scalable, secure, reliable, responsible, and aligned with organizational priorities.

Listed skills

• The posting lists machine learning, AI governance, and data science.