Your key responsibilities
- Design, develop and implement AI and Gen-AI based Agentic software systems on the cloud.
- Collaborate with other development teams and SMEs to integrate shared services into products.
- Learn Deutsche Bank’s AI Governance framework and operate within safe AI principles.
- Leverage architecture decision trees to pick strategic AI patterns to solve business problems.
- Integrate Gen-AI APIs with cloud-native presentation (GKE, Cloud Run) and persistent layers (PostgreSQL, BQ).
- Run systems at scale while continuing to innovate and evolve.
- Work with data engineers and scientists to ensure effective data collection and preparation for training AI models.
- Continuously monitor the performance of AI solutions and implement improvements.
- Lead training sessions and create comprehensive documentation to empower end users.
- Function as an active member of an agile team.
Your skills and experience
Skills You’ll Need
- AI Expertise: Proficiency in frameworks (Langchain, Streamlit or similar), libraries (Scikit-learn or similar) and cloud platforms (Vertex AI or OpenAI).
- Prompt Engineering & RAG: Skills in crafting effective prompts and enhancing AI outputs with external data integration.
- NLP Knowledge: Strong understanding of natural language processing and conversational AI technologies.
- Deployment & Operations: Experience in model deployment, monitoring, optimization (MLOps), and problem-solving.
- Proficiency with cloud-native orchestration systems (Docker/Kubernetes).
- Proficiency in Python or Java, and SQL.
- Knowledge of RESTful design.
- Experience working with different types of enterprise and real-world data sets – structured, semi-structured and unstructured data.
- Experience putting ML/AI into production, and ability to talk through best practices and pitfalls.
- Relationship and consensus building skills.
Skills That Will Help You Excel
- Stakeholder Communication: Ability to explain AI concepts to non-technical audiences and collaborate cross-functionally.
- Adaptability & Innovation: Flexibility in learning new tools and developing innovative solutions.
- Experience with cloud-native databases/warehouses (PG and BigQuery).
- Experience in data visualization and observability with a focus on real time serving and monitoring of time series data with alerts.
- Thought Leadership & Advocacy: Develop awareness of industry developments and best practices Provide thought leadership in emerging technologies as they relate to AI topics.