AI Solutions Lead Engineer

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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