Generative AI Solutions Engineer (m/f/d) - 883160/1

Data and AI are increasingly central to our ability to deliver better outcomes for customers and to improve operational efficiency. This role designs, delivers, and scales data and generative AI solutions that unlock real-time customer insights, streamline internal data access, and accelerate compliant knowledge and content creation across Operations and Customer Experience (CX).

Building on the global strategy, the Generative AI Solutions Engineer within CX in Operations collaborates closely with global data and digital teams, IT, R&D, and Legal/Compliance to develop robust data products and AI-enabled applications that are secure, reliable, and aligned with business priorities.

The Generative AI Solutions Engineer turns complex data into actionable insights, builds standardized, scalable dashboards and AI-assisted workflows, and manages delivery of generative AI solutions for knowledge management and analytics. The role leads AI and analytics projects end-to-end, gathers and translates requirements, communicates clearly with technical and non-technical stakeholders, and drives continuous improvements in model performance, data quality, and governance to support superior digital service execution and customer experience.

• Develop and maintain generative AI-enabled applications and analytics solutions, including LLM-powered RAG, secure enterprise search, and agentic workflows leveraging tools, planning and orchestration
• Design, build and operate AI-first data pipelines (e.g. Azure, Databricks, PySpark), including pre-processing of unstructured data, chunking, embedding and vector indexing; incorporate synthetic data creation to enhance training and evaluation
• Implement continuous evaluation and observability across AI systems (accuracy, groundedness, latency, cost); publish KPIs and convert user feedback into structured improvement cycles
• Proactively engage and manage stakeholders; capture business requirements and translate them into technical solutions that deliver measurable customer
• and operational impact; present complex AI concepts clearly to non-specialist audiences
• Implement regulatory, data privacy and responsible AI compliance in close collaboration with Legal, Privacy and Information Security; ensure appropriate controls and documentation
• Develop and maintain AI-enabled monitoring tools and dashboards to surface emerging customer issues, risk signals and recurring themes across CX
• Design and implement AI-augmented development workflows — using agentic coding tools and LLM-based code generation — to accelerate team delivery; establish best practices for reviewing and validating AI-generated code
• Create training resources, conduct enablement sessions and maintain technical documentation; standardize analytics and AI delivery across CX and the broader CoE
• Collaborate with team members to co-design solution architectures, define success metrics and drive continuous improvement

Must haves:

• Education in quantitative field or applied sciences
• 5+ years in an analytical/technical role with proven experience delivering data and AI solutions end-to-end.
• Hands-on experience building cloud data pipelines and analytics products (e.g., Azure, Databricks, PySpark).
• Practical experience with generative AI/LLMs in enterprise settings (e.g., RAG, prompt engineering, evaluation and monitoring).
• Knowledge in analyzing product data
• Experience managing projects and working with diverse set of senior stakeholders on requirements, roles and responsibilities, project timelines
• Passionate and curious about data and its value in improving people’s lives
• Appetite to immerse in a problem and tackling it by designing and developing results or solutions starting from a blank page
• Ability to effectively adapt to change and willingness to learn and apply new technologies, processes and tools
• Flexible and resilient with strong sense of accountability
• Able to communicate technical aspects succinctly to both technical & non-technical stakeholders
• Ability to interact effectively with others, working in an international, highly diverse, and globally dispersed team
• Ability to challenge others and provide honest feedback in a constructive way
• Ability to use own judgement and best practice to make proactive decisions independently
• Hands-on experience in generative AI techniques, including LLMs, embeddings, vector databases and RAG architectures; ability to evaluate and monitor LLM/system outputs for accuracy, bias and usefulness.
• Experience with Databricks and PySpark; familiarity with cloud platforms (Azure).
• Proven ability of deriving insights from diverse data sources and translating them into clear and precise conclusions and recommendations
• Passionate about data and an engaging communicator with strong work ethic
• Excellent presentations skills and able to build credibility with business stakeholders
• Ability to work independently and effectively across projects while managing conflicting priorities
• Ability to orchestrate agentic coding assistants (e.g. GitHub Copilot, Claude Code) to accelerate delivery, paired with strong judgment to review and own AI-generated code.
• Fluent in English
• Python (incl. Pandas) or R
• Databricks with PySpark for large-scale data processing
• Generative AI toolkit: Azure OpenAI or equivalent; hands-on implementation of RAG (embeddings, chunking, grounding) with vector search (Azure AI Search or equivalent)
• Agentic coding tools: GitHub Copilot, Claude Code or equivalent
• Version control with Git; collaborative workflows (branching, pull requests); CI/CD for data/AI apps
• Understanding of network/security hygiene in Azure
• Agile tooling and collaboration: JIRA (or similar) and Confluence
• Microsoft 365 (Excel, PowerPoint)