AI/ML Engineer

Must have Skills:

Designing and Building LLM and AI Solutions

• You design, develop and implement Business AI solutions that fit within the architecture, standards and governance of the AI Centre of Excellence.
• You build LLM applications, retrieval and prompt patterns, evaluation flows and agentic components for concrete business use cases.
• You translate business and process challenges into technically robust solutions with attention to reliability, scalability and maintainability.
• You develop reusable building blocks, templates and reference implementations so that teams can deliver AI solutions faster and more consistently.

MLOps, LLMOps and Platform Integration

• You set up CI/CD-like processes, deployment pipelines, model and prompt version management and release approaches for AI and LLM solutions.
• You build and manage pipelines for data, model and application integration and ensure that solutions align well with the AI platform and surrounding systems.
• You support the operationalisation of experiments into production, including testing, validation, deployment, rollback and management.
• You help establish standards for observability, evaluation, lifecycle management and repeatable delivery of AI solutions.

Quality, Evaluation and Monitoring

• You develop evaluation approaches for models and LLM solutions, including quality measurements, test scenarios, guardrails and acceptance criteria.
• You monitor performance, usage, costs, reliability and output quality and translate these insights into improvement actions.
• You help manage risks related to drift, hallucinations, prompt sensitivity, integration errors and undesired output.
• You contribute to an engineering approach in which testing, measurement and controlled improvement are fixed parts of the AI lifecycle.

Governance, Security and Responsible Operationalisation

• You implement technical measures that contribute to governance, security, privacy, logging, auditability and responsible use of AI solutions.
• You ensure that solutions align with agreed architecture principles, risk frameworks and approval processes for Business AI and agentic AI.
• You help safeguard human oversight, transparency and manageability where AI solutions impact processes, customers or decision-making.
• You support the translation of policies and guidelines into practical engineering choices and technical guardrails.

Collaboration and Acceleration of Business AI

• You collaborate with business stakeholders, data engineers, architects, security, platform teams and other CoE roles to successfully deliver use cases.
• You help accelerate the realisation of business use cases by making technical feasibility transparent at an early stage and by providing reusable solutions.
• You document choices, patterns and lessons learned so that knowledge becomes reusable and the organisation’s engineering maturity grows.
• Within your domain, you are an important link in building a controlled, scalable AI capability that delivers sustainable business value.