AI Solutions Engineer

Working closely with business leaders, operational teams, IT, and Global Digital Innovation teams, you will design, prototype, and deploy practical AI-powered solutions that improve operational efficiency, simplify workflows, and modernize legacy processes. As an AI Solutions Engineer, you will accelerate business value delivery by rapidly turning ideas into AI-enabled applications, workflow automation solutions, and modern digital capabilities.

Tradebe is a group of industrial businesses with the commitment of creating a more sustainable planet and making significant contributions to human wellbeing. In the US, we are leaders focused on recycling and circular economy, managing all different environmental liabilities in a sustainable way.

What will you do? Make an impact!

As an AI Solutions Engineer, you will accelerate business value delivery by rapidly turning ideas into AI-enabled applications, workflow automation solutions, and modern digital capabilities. Working closely with business leaders, operational teams, IT, and Global Digital Innovation teams, you will design, prototype, and deploy practical AI-powered solutions that improve operational efficiency, simplify workflows, and modernize legacy processes.

This role is highly hands-on and execution-focused. You will rapidly translate ambiguous business problems into scoped experiments, MVPs, and scalable production-ready solutions. You will work across the full solution lifecycle: from idea and prototyping through deployment, operationalization, monitoring, and continuous improvement.

Key Responsibilities

Rapid Prototyping & MVP Delivery

• Develop and deliver rapid AI prototypes and demo-ready MVPs that validate business value quickly and support fast iteration with business stakeholders.
• Translate ambiguous business challenges into working solutions, and scalable applications.

AI Application Development

• Build, deploy, and maintain AI-enabled applications, workflow automation solutions, and user-facing tools that improve operational efficiency and business processes.
• Develop end-to-end solutions leveraging modern AI technologies including large language models (LLMs), retrieval-augmented generation (RAG), APIs, orchestration frameworks, and AI-assisted automation.

Workflow Automation & Legacy Modernization

• Replace or simplify legacy internal applications with fit-for-purpose solutions while implementing AI-assisted workflow automation and modern user experiences.
• Design solutions that reduce manual effort, simplify complex workflows, and improve usability for business users.

Enterprise Integration & Operationalization

• Integrate AI solutions with enterprise applications, operational platforms, and data environments while ensuring solutions are scalable, secure, maintainable, and production-ready.
• Establish observability, monitoring, governance, and operational controls to support long-term reliability and supportability.

Cross-Functional Collaboration

• Partner with business teams, BRMs, IT, architecture, security, and Global Digital Innovation teams to align technical solutions with operational needs and governance standards.
• Serve as a technical translator between business stakeholders and technical teams to accelerate solution adoption and execution.

AI Governance & Responsible AI

• Support AI governance initiatives including approved tools and models, vendor evaluation, data privacy, security controls, and value realization tracking.
• Ensure AI deployments align with company security, compliance, and operational standards.

Production Readiness & Continuous Improvement

• Ensure solutions meet operational requirements for accuracy, resiliency, maintainability, usability, and cost efficiency.
• Continuously iterate and improve deployed solutions based on business feedback and operational performance.

Training & Capability Building

• Upskill IT teams and business stakeholders through hands-on collaboration, reusable templates, practical examples, and build-together approaches.
• Help establish reusable patterns and best practices that enable broader AI adoption across the organization.

Do you have what it takes?

• Education: Bachelor's degree in Computer Science, Engineering, Information Systems, or equivalent hands-on experience preferred.

• Experience:
  • 3+ years of hands-on software development experience across backend, frontend, and data layers.
  • 1+ years of experience delivering applied AI solutions such as Generative AI, Retrieval-Augmented Generation (RAG), AI-assisted automation, intelligent search, or workflow orchestration solutions.
  • Experience building and integrating solutions using APIs, AI frameworks, orchestration platforms, and enterprise data sources.
  • Experience modernizing or replacing legacy/internal applications with scalable, maintainable solutions.
  • Experience with cloud platforms, low-code/no-code automation tools, orchestration frameworks, observability tooling, or enterprise integrations is a plus.