AI Engineer

Power Platform Lead The Opportunity Most Power Platform initiatives never get the investment they deserve. They start as shadow IT, stay siloed in one department, and never scale into anything strategic. This role is different. You'll build a Center of Excellence from the ground up, with a genuine mandate to govern, scale and modernise Power Platform and Copilot Studio across the business. The Role You'll take ownership of Power Platform and Copilot Studio end to end: Build and run the Center of Excellence, covering governance and lifecycle management of apps, flows and bots Develop internal AI assistants in Copilot Studio, including department-specific Copilots Step up to Microsoft Foundry and Agent 365 when Power Platform reaches its limits Launch and grow a citizen development programme across operational and central departments, including training and reviews Set the standards: reusable templates, connectors and security guidelines Connect it all to Microsoft 365, Azure and the organisation's specialised applications Own reporting on usage, security and quality The Company You'll join an internationally operating organisation as it builds serious digital transformation and AI capability from the ground up. Power Platform and Copilot Studio have already earned trust here, and now it's time to professionalise and scale them. You'll have genuine autonomy to shape how AI and automation work across the business, not just maintain what already exists. What You'll Need 4+ years' experience with Power Platform (Power Apps, Power Automate, Power BI, Power Pages, Virtual Agents) Experience with Copilot Studio and Microsoft Foundry, or similar A track record setting up and running a Center of Excellence, ideally using the CoE Starter Kit Solid Microsoft 365 and Azure knowledge, including identity, security and licensing Fluent English and German (C1/C2) How to Apply Your CV doesn't need to be up to date. Send what you have, or give the team at MAM Gruppe a call for a confidential chat about the role.

AI Engineer / Data Scientist The Opportunity A lot of AI engineering roles are really just MLOps maintenance dressed up in a flashier job title. This one isn't. You'll be designing and building AI systems that sit at the heart of a financial data platform, working across the full stack from LLM architecture and RAG pipelines through to cloud infrastructure and production deployment. If you want to work on problems that are genuinely complex, in an environment that takes engineering quality seriously, this is worth a look. The Role You'll design, build, and productionise machine learning and generative AI solutions, working closely with data scientists, product owners, and business stakeholders. That means taking models from prototype to production, building the MLOps pipelines to keep them running reliably at scale, and making sure the systems you build integrate cleanly with core financial data platforms and downstream applications. You'll also be evaluating and implementing LLM-based solutions - RAG architectures, fine-tuning, prompt engineering - for both internal tooling and client-facing use cases, contributing to AI governance and responsible AI practices in a regulated environment, and mentoring junior engineers as the team grows. The role sits at the intersection of serious engineering and applied AI - and the expectation is that you're genuinely interested in both sides of that. The Company Our client is an established business operating in the financial services space, working with data and technology at enterprise scale. They're investing seriously in AI and building the engineering capability to match - which means joining now puts you close to decisions that matter, rather than inheriting a system someone else already built. What You'll Need 4+ years of professional engineering experience, with at least 2 years focused on AI/ML systems in production Strong Python skills and a track record of writing production-quality code Hands-on experience with ML frameworks such as PyTorch, TensorFlow, or scikit-learn Practical experience with LLMs, including prompt engineering, RAG architectures, and/or fine-tuning Experience building and maintaining MLOps pipelines using tools such as MLflow, Kubeflow, or Vertex AI Pipelines Strong cloud platform experience on AWS, Azure, or GCP, ideally in a financial services or regulated context Proficiency with Docker, Kubernetes, and CI/CD tooling Fluency in German and English at professional level How to Apply Send your CV to the MAM Gruppe team. It doesn't need to be up to date - send what you have, or just get in touch for a conversation.

AI Execution Manager Location: Bavaria Our client is seeking an AI Execution Manager to support the implementation of AI and digital transformation initiatives across the organisation. This role focuses on translating AI opportunities into practical business solutions and driving the operational delivery of data- and AI-driven projects. Key Responsibilities: Identify and prioritise AI and digitalisation opportunities across business functions. Support the end-to-end implementation of AI use cases and transformation initiatives. Coordinate stakeholders across business, IT and data-focused teams. Facilitate workshops, use-case discussions and implementation activities. Support the integration of AI solutions into existing systems and processes. Contribute to AI enablement, knowledge sharing and digital capability development. Collaborate with internal and external stakeholders on strategic AI initiatives. Drive continuous improvement and support scalable AI adoption across the organisation. Your Profile: Experience within AI, digital transformation or data-driven project environments. Strong understanding of AI, automation or digital technologies and their business application. Experience managing projects within agile or technology-focused environments. Strong analytical, communication and facilitation skills. Ability to translate business requirements into practical digital solutions. Collaborative, proactive and solution-oriented working style. Familiarity with agile methodologies such as Scrum or Kanban would be advantageous. Fluent German and English language skills. What’s on Offer? Exposure to innovative AI and digital transformation initiatives. Modern and collaborative working environment. Opportunity to shape AI adoption across the organisation. Long-term development and progression opportunities.

Data Scientist Location: Germany / Remote Our client is seeking a Data Scientist to support the development of predictive models and data-driven analytics solutions within a fast-paced environment. This role focuses on time series analysis, machine learning and the application of modern AI approaches to large-scale datasets. Key Responsibilities: Develop and optimise predictive models and analytical frameworks. Analyse large datasets to identify patterns, trends and actionable insights. Support forecasting and modelling initiatives using statistical and machine learning techniques. Work with structured and unstructured data sources, including text-based datasets. Conduct backtesting, validation and performance optimisation of models. Collaborate with technical and business stakeholders on data-driven initiatives. Contribute to the evolution of modern AI and analytics capabilities. Your Profile: Strong experience within data science, quantitative analysis or statistical modelling environments. Expertise in time series analysis and forecasting techniques. Strong Python programming skills. Experience with machine learning and AI-related technologies. Analytical, hands-on and solution-oriented mindset. Ability to work independently and take ownership of projects. Strong communication and collaboration skills. What’s on Offer? Flexible remote working environment. Exposure to modern AI and advanced analytics projects. High level of ownership and influence within the role. Long-term development and growth opportunities.