AI Engineer

Key Responsibilities

• Build, configure, test, and deploy AI solutions that address priority Corporate Affairs use cases, translating requirements and designs into working applications and workflows.
• Own front-end, user interface development, building user-facing applications end-to-end.
• Partner with the AI Enablement team to turn business priorities into technically sound solutions that can move efficiently from prototype to production.
• Integrate AI models, enterprise platforms, and approved data sources to create solutions that are reliable, connected, and practical for day-to-day use.
• Develop and refine prompts, logic, workflows, and evaluation approaches to improve output quality, usability, and consistency across deployed solutions
• Support rapid experimentation and prototyping while maintaining a clear path to production, ensuring promising ideas can be scaled without unnecessary rework.
• Monitor solution performance, troubleshoot issues, and continuously optimize reliability, speed, and output quality after launch
• Implement testing, documentation, and release discipline so solutions are maintainable, auditable, and easier to scale across the portfolio.
• Work closely with business users to gather feedback, improve functionality, and ensure delivered solutions meet real operational needs and adoption goals.
• Apply responsible AI, security, and data handling requirements throughout development, ensuring solutions meet internal policy and compliance expectations.

Essential Requirements:

• Bachelor’s degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Engineering, or a related technical field, or equivalent practical experience.
• Relevant certifications in AI/ML, cloud platforms, data engineering, or software engineering.
• 5-8 years of hands-on experience in AI engineering, machine learning engineering, software engineering, or data engineering roles, with at least 3 years building and deploying production-grade AI, generative AI, or advanced analytics solutions in a corporate environment.
• Extensive experience with AI platforms or toolchains (Claude, GPT, Azure OpenAI, Langfuse, vector databases etc.)
• Strong hands-on experience with large language models, prompt design, workflow orchestration, model integration, evaluation approaches, and production support for AI-enabled applications.
• Proven experience developing, testing, deploying, and optimizing reliable technical solutions that meet business requirements and perform effectively in day-to-day use.
• Experience working with enterprise data sources, APIs, cloud platforms, and application integration patterns required to operationalize AI solutions at scale.
• Experience monitoring live solutions, resolving production issues, and continuously improving performance, usability, and output quality after launch.

Desirable Requirements:

• Demonstrated ability to move use cases from prototype through production, balancing experimentation with engineering discipline, maintainability, and control requirements.
• Proven track record of delivering measurable outcomes through AI or advanced technology solutions in a business context.
• Experience working with cross-functional stakeholders including product owners, architects, data teams, IT, and business users in agile or delivery-oriented environments.
• Exposure to Corporate Affairs, communications, or content-centric business processes is preferred but not essential.