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AI Solutions Lead Engineer – Durbanville – Cape Town - … in Cape Town - Image 1
AI Solutions Lead Engineer – Durbanville – Cape Town - … in Cape Town - Image 1
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AI Solutions Lead Engineer – Durbanville – Cape Town - …

AI Solutions Lead Engineer – Durbanville – Cape Town - …
Description

ENVIRONMENT:

Our client who specializes in end-to-end engineering for medium and heavy-duty 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.

 

DUTIES:

AI Strategy & Opportunity Identification

  • 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

Business Case Development

  • 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

Stakeholder & Vendor Management

  • 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

AI Solution Implementation & Change Management

  • 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

Innovation & AI Advocacy

  • 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

AI Solution Governance & Management

  • 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

AI Market Research & Technology Evaluation

  • 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

AI Product Ownership

  • 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

Specialist-Agent Management

  • 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

Knowledge Management & Engineering Content Ownership

  • Curate engineering knowledge repositories, standards, taxonomies, and authoritative information sources
  • Maintain source quality and knowledge governance practices
  • Identify and nominate engineering content for AI knowledge integration

SME Validation & Continuous Improvement

  • Lead subject matter expert validation and review processes
  • Identify knowledge gaps and opportunities for enhancement
  • Define feedback mechanisms, review queues, and continuous improvement processes
  • Support learning-loop initiatives for ongoing AI optimisation

Use-Case Analysis & Solution Design

  • Participate in AI use-case intake, classification, and evaluation processes
  • Assess whether solutions require deterministic automation, probabilistic AI reasoning, or hybrid approaches
  • Contribute domain expertise to workflow orchestration and routing design

Adoption & Benefits Realisation

  • Drive AI adoption, user engagement, and behavioural change initiatives
  • Monitor KPI achievement and business value realisation
  • Collect user feedback and identify improvement opportunities
  • Ensure AI initiatives deliver measurable business outcomes and operational benefits

 

 

REQUIREMENTS:

Qualifications, Experience and Skills:

  • Bachelor's or Master's degree in Business, Engineering, Innovation, Operations, or a related field.
  • 5+ years of experience in operations, product development, innovation, continuous improvement, or business transformation preferably in manufacturing or engineering environments.
  • Proven ability to lead cross-functional initiatives and manage external technology partners.
  • Fluent in English, with exceptional written, verbal, and interpersonal communication skills, capable of engaging confidently across technical and executive audiences.
  • Experience in product ownership, backlog management, or business analysis able to define requirements, prioritise work, and track outcomes.
  • Able to influence technical and business domains.

 

ATTRIBUTES:

  • Strong business instincts and engineering curiosity.
  • Naturally curious, hands-on, and relentless about solving real problems.
  • Not afraid of technology, but more focused on what it enables rather than how it works under the hood.
  • Attention to detail and accuracy in work.
  • Ability to handle confidential information with discretion.
  • Excellent organisational and multitasking abilities.
  • Outstanding time management skills.

Willingness to travel internationally

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AI Solutions Lead Engineer – Durbanville – Cape Town - … has been posted in the Cape Town Engineering category on Locanto.

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