Applied AI Solutions Specialist

Mott MacDonald • New York, NY

1d • $137,000 - $168,000

About The Position

The Applied AI Solutions Specialist works with AEC project teams and disciplines across Mott MacDonald’s North America region to identify, develop, and adopt practical AI solutions that improve project delivery. Working alongside engineers, designers, and construction professionals, the specialist learns current workflows and transforms project and discipline processes into AI-enabled ways of working.

The role determines whether AI is appropriate and selects the right approach, from existing enterprise capabilities and configurable AI solutions to custom development when justified. It rapidly prototypes with real project information, supports adoption, and works with the Solution Delivery team to scale proven solutions. The role reports to the AI and Information Leader.

The ideal candidate combines a strong AEC background with hands-on applied AI and software development capability, and can independently turn complex project problems into practical, working solutions.

Requirements

• Bachelor’s degree in Engineering, Construction Management, Architecture, Computer Science, Artificial Intelligence, Data Science, Information Systems, or a related field.
• Experience in architecture, engineering, construction, or major infrastructure delivery, with a practical understanding of multidisciplinary project design and delivery.
• Strong understanding of design and/or construction workflows, including how teams develop, coordinate, review, approve, issue, and use project information.
• Practical knowledge of AEC systems, including CAD/BIM, Common Data Environments, document management, GIS/spatial, and other engineering or project information systems.
• Experience with AEC information formats, including drawings, BIM/CAD models, specifications, requirements, calculations, schedules, documents, spatial data, imagery, and structured project data.
• Strong hands-on experience building AI solutions using Python, AI APIs, SDKs, and modern frameworks, including agentic, multi-step, and tool-enabled workflows.
• Experience applying Generative AI and LLMs to real technical or engineering problems, including retrieval and grounding, structured outputs, tool calling, and multimodal AI.
• Ability to rapidly prototype independently, move from ambiguous problems to working proofs of concept, and investigate unfamiliar engineering problems, formats, systems, and technologies.
• Ability to integrate AI with project information, APIs, automation, and existing applications into end-to-end solutions.
• Ability to select the right approach across enterprise, configurable, and custom AI, and recognize when AI is not the right solution.
• Understanding of AI evaluation, including accuracy, reliability, false positives and negatives, traceability, limitations, and the role of human and engineering validation.
• Proven ability to work with project and discipline teams to understand workflows, co-develop solutions, incorporate feedback, and support adoption of AI-enabled ways of working.
• Ability to translate between AEC practitioners and technical teams, keeping solutions grounded in project needs while viable and scalable.
• Clear communication of technical concepts, limitations, and findings to technical and non-technical stakeholders, with curiosity and an ability to learn new technologies and engineering domains quickly.
• Authorization to work for any employer in the United States; sponsorship is not available.

Nice To Haves

• Relevant postgraduate qualifications or professional certifications in engineering, AI, machine learning, software development, or digital delivery.
• Experience applying AI, machine learning, or automation directly within engineering design, construction, or infrastructure projects.
• Experience prototyping use cases such as design checking, drawing review, requirements assessment, specification analysis, engineering information retrieval, construction information analysis, or automated quality checking.
• Computer vision or multimodal AI applied to drawings, models, imagery, point clouds, or video.
• RAG, knowledge-retrieval, AI agent, or tool-enabled solutions grounded in controlled project information.
• Familiarity with Microsoft 365 Copilot, Copilot Studio, and Azure AI Foundry, and understanding which problems suit enterprise, configurable, or custom AI.
• Familiarity with Autodesk Construction Cloud, Civil 3D, Revit, ProjectWise, ArcGIS, or SharePoint.
• SQL, databases, vector search, and data platforms supporting AI applications.
• Experience transitioning prototypes to solution delivery teams for productionisation and cross-project scaling.
• Understanding of responsible AI, information security, data governance, and engineering assurance considerations.

Responsibilities

• Work with engineering, design, and construction teams to understand current workflows and delivery challenges, and identify where AI can improve quality, efficiency, consistency, or access to information.
• Assess whether AI is appropriate and select the simplest viable approach, using existing enterprise capabilities, configurable solutions, automation, engineering applications, or custom AI as appropriate.
• Redesign project and discipline processes as AI-enabled workflows that combine AI, automation, engineering technologies, project information, and human expertise.
• Build, test, and iterate prototypes with the engineers, designers, and construction professionals who will use them, demonstrating technical feasibility and project value.
• Work with AEC information including drawings, BIM/CAD models, specifications, requirements, calculations, GIS and spatial data, imagery, schedules, and structured project data.
• Determine where AI adds value and combine it with deterministic logic, automation, APIs, conventional development, or existing engineering applications as appropriate.
• Adapt prototypes to project-specific information, standards, systems, and practices; support adoption through demonstrations, user testing, feedback, workflow refinement, and barrier resolution.
• Validate AI outputs with engineers and subject-matter experts, understand limitations, and establish traceability, assurance, and human review before solutions are relied upon.
• Transition proven solutions to the Solution Delivery team by providing prototype components, technical knowledge, requirements, user feedback, project context, and lessons learned.
• Help adapt proven solutions for other projects with different standards, workflows, information structures, systems, and client requirements.
• Capture reusable technical approaches, workflow patterns, prototype components, and lessons learned, and evaluate emerging AI technologies for AEC delivery.

Benefits

• Performance-based bonuses.
• Medical coverage.
• Dental coverage.
• Vision coverage.
• Flexible spending accounts (FSA) and health savings accounts (HSA).
• Company-paid life insurance.
• Short-term and long-term disability coverage.
• Competitive 401(k) plan with company matching.
• Paid time off.
• Paid holidays.
• Caregiver leave.
• Employee referral bonuses.
• Professional registration and membership reimbursements.
• Tuition assistance for continued learning and career development.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level