Group AI/ML Solutions Architect - MySQL (126126)

Foundational AI/ML & Software Engineering Strong grounding in ML fundamentals and software engineering, enabling translation of business problems into robust, scalable AI/ML solutions Experience in designing, building and integrating production-grade systems using modern engineering practices (APIs, microservices, CI/CD, containerization) Ability to bridge classical ML approaches with emerging GenAI paradigms, applying the right techniques to deliver reliable and maintainable solutions Effectively leverage AI-assisted development tools (e.g., GitHub Copilot, Claude Code) to accelerate prototyping, improve engineering quality and enhance developer productivity

Strong grounding in ML fundamentals and software engineering, enabling translation of business problems into robust, scalable AI/ML solutions

Experience in designing, building and integrating production-grade systems using modern engineering practices (APIs, microservices, CI/CD, containerization)

Ability to bridge classical ML approaches with emerging GenAI paradigms, applying the right techniques to deliver reliable and maintainable solutions

Effectively leverage AI-assisted development tools (e.g., GitHub Copilot, Claude Code) to accelerate prototyping, improve engineering quality and enhance developer productivity

Product Collaboration & Enablement Ability to work effectively within agile product teams, collaborating in iterative cycles to refine requirements, validate hypotheses and deliver incremental AI/ML value Ability to drive alignment independently across product, AI/ML engineering, platform and MLOps teams to achieve shared engineering outcomes Strong capability in early-stage AI/ML solution development, including problem framing, feasibility assessment, rapid prototyping and iterative experimentation Effective collaboration across geographically distributed teams (Denmark, India, Portugal), with strong cross-cultural awareness and communication

Ability to work effectively within agile product teams, collaborating in iterative cycles to refine requirements, validate hypotheses and deliver incremental AI/ML value

Ability to drive alignment independently across product, AI/ML engineering, platform and MLOps teams to achieve shared engineering outcomes

Strong capability in early-stage AI/ML solution development, including problem framing, feasibility assessment, rapid prototyping and iterative experimentation

Effective collaboration across geographically distributed teams (Denmark, India, Portugal), with strong cross-cultural awareness and communication

LLM Systems Architecture & Delivery Architect scalable, reliable GenAI systems with focus on performance, cost, latency and user experience Establish reusable design patterns and frameworks for building and scaling agentic and LLM-based solutions Drive end-to-end delivery of GenAI systems from prototyping to production adoption

Architect scalable, reliable GenAI systems with focus on performance, cost, latency and user experience

Establish reusable design patterns and frameworks for building and scaling agentic and LLM-based solutions

Drive end-to-end delivery of GenAI systems from prototyping to production adoption

GenAI & Agentic Systems Design Design and build generative AI and agent-based that support reasoning, planning and semi-autonomous execution of complex workflows Apply advanced techniques including RAG, prompt orchestration, memory management and tool/agent coordination Translate business problems into intelligent AI workflows combining human-in-the-loop and autonomous decision-making Apply responsible AI practices, including guardrails, bias mitigation, and safe system behavior Ability to implement end-to-end ML workflows, including data preprocessing, model development, evaluation and deployment, with support for HITL and decision-support systems Good to have: experience with document intelligence and NLP/LLM use cases such as contract analytics, automated information extraction, intelligent document processing, semantic search and AI-driven automation workflows

Design and build generative AI and agent-based that support reasoning, planning and semi-autonomous execution of complex workflows

Apply advanced techniques including RAG, prompt orchestration, memory management and tool/agent coordination

Translate business problems into intelligent AI workflows combining human-in-the-loop and autonomous decision-making

Apply responsible AI practices, including guardrails, bias mitigation, and safe system behavior

Ability to implement end-to-end ML workflows, including data preprocessing, model development, evaluation and deployment, with support for HITL and decision-support systems

Good to have: experience with document intelligence and NLP/LLM use cases such as contract analytics, automated information extraction, intelligent document processing, semantic search and AI-driven automation workflows