SUMMARY:
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POSITION INFO:
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
