AI Solutions Lead Engineer – Durbanville Onsite

ENVIRONMENT:

Our client who specializes in end-to-end engineering for medium and heavy‑dutiful platforms is seeking a business-oriented, innovation-driven problem solver to join them as an AI Solutions Lead Engineer. The ideal candidate will have a deep understanding of how manufacturing and engineering businesses operate and how complex workflows function, bringing structured problem‑solving and hands‑on thinking to the table. This position is business‑driven and focused on operational strategy, engineering product ownership, and innovation.

It is not a software or coding position. It is specifically not suited to persons pursuing programming or data science, as it does not involve coding or technical model deployment; it does, however, require owning prompt design, decision thresholds, curated knowledge inputs, response structures, and evaluation criteria.

• Identify high‑value AI use cases across engineering, operations, HR, finance, and business development functions
• Engage with teams and map workflows to uncover opportunities for productivity improvement, automation, business insights, and competitive advantage
• Analyse industry and business trends and translate opportunities and challenges into structured problem and solution statements
• Assess operational processes, constraints, and technologies to determine AI solution viability
• Design, pilot, and refine AI‑enabled workflows in collaboration with business stakeholders

• Prioritise AI opportunities based on business impact, effort, and speed to value
• Develop ROI‑driven business cases aligned with operational objectives
• Present recommendations and strategic opportunities to senior leadership and stakeholders

• Identify, evaluate, and collaborate with AI vendors, technology providers, and subject matter experts
• Act as the primary liaison between business units and AI delivery teams
• Translate business requirements into solution objectives and requirements
• Ensure solutions remain aligned with agreed business outcomes

• Lead discovery, design, pilot, and rollout activities for AI initiatives
• Define success metrics and monitor implementation progress
• Identify and remove execution roadblocks
• Develop and deliver training programmes to support AI adoption and capability development
• Drive organisational change management and user engagement initiatives

• Promote practical understanding and adoption of AI across the organisation
• Facilitate workshops, demonstrations, and awareness sessions
• Encourage innovation, experimentation, and continuous improvement practices
• Foster a culture of AI‑enabled business transformation

• Oversee AI tools, licensing, access management, and approved use cases
• Monitor adoption, effectiveness, compliance, and risk associated with AI solutions
• Drive corrective actions where required
• Ensure AI solutions remain scalable, practical, and aligned with business objectives

• Monitor emerging AI technologies, tools, and industry developments
• Evaluate new AI platforms and capabilities against business requirements
• Identify practical, high‑value innovations for implementation
• Ensure the organisation remains competitive and current in AI adoption

• Own the engineering AI product vision, roadmap, and backlog priorities
• Prioritise specialist‑agent capabilities and AI use cases based on business value and urgency
• Define MVP requirements and phased delivery approaches
• Collaborate with technical teams on feasibility, dependencies, and delivery planning

• Define specialist‑agent prompts, thresholds, knowledge sources, response structures, and evaluation criteria
• Manage specialist‑agent content and domain configurations
• Establish escalation, abstention, and human‑review requirements
• Participate in specialist‑agent tuning and optimisation initiatives

• Curate engineering knowledge repositories, standards, taxonomies, and authoritative information…