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Join the Advanced Analytics & AI Tribe at RBI Group, where the innovation of a start-up meets the stability of an established financial institution. We are seeking a senior data scientist to design and deliver agentic AI solutions in our use case teams, leveraging MCP and modern agent frameworks to solve high-impact problems across our network banks. If you are passionate about building agentic AI systems—combining LLMs, RAG, and MCP-enabled tool integrations—and turning complex business problems into reliable, production-grade solutions, this role is for you.
Your mission at RBI:
- End-to-end ownership of ML/AI/agentic use cases: framing to production.
- Implement MCP and orchestrate LLMs/tools with agent frameworks (LangChain, LlamaIndex, Semantic Kernel, OpenAI Assistants), including function calling, fallbacks, and guardrails.
- Build and optimize RAG; evaluate for precision/recall and latency.
- Establish LLMOps/MLOps (experiments, versioning, CI/CD, registries, monitoring, incident response) and ensure reliability, safety, and compliance (prompt-injection defenses, content filtering, policy, red teaming, quality gates).
- Run rigorous offline/online evaluations (backtests, time-series CV, A/B, shadow/canary), monitor drift/impact, and optimize performance/cost (latency, throughput, rate limits, batching, streaming, caching) with usage/cost dashboards.
- Interact with Business Partner to Define requirements.
Your core competencies:
- 5+ years delivering ML/AI systems in production; experience in financial services is an asset.
- Expert Python skills; SQL/PySpark; Spark/Databricks and expertise in DS/ML/LLM.
- Practical experience with GenAI models and pipelines and agentic AI (architectures, planning, memory, tool use, multi-agent orchestration).
- Hands-on with agent frameworks and tooling (LangChain, LlamaIndex, CrewAI or similar), prompt engineering, function/tool calling, and evaluation harnesses.
- RAG expertise: embeddings, vector stores, retrieval, and evaluation approaches.
- LLMOps / MLOps experience: MLflow or similar, feature stores, data/prompt versioning, CI/CD (GitHub Actions, Jenkins), Docker, orchestration tools (Airflow, Prefect).
- Experience designing evaluation and validation frameworks: backtesting, out-of-sample testing, A/B, drift detection.
- Ability to translate business requirements into production-grade technical solutions and to manage stakeholder relationships; fluent English required, German is an advantage.
Nice to Have:
- Knowledge of Responsible AI and regulatory frameworks (EU AI Act, model risk, data privacy).
- Banking domain familiarity (risk, fraud, customer analytics, operations) and cost/benefit tracking.
- Software and data engineering foundations: APIs (REST/gRPC), microservices, testing, logging and tracing.
- Experience with containers and orchestration (Docker, Kubernetes).
What´s in it for you:
- Flexible work week: Flexible hours, work-from-home options from Austria, and 30 days/year remote work from any EU country.
- Global community: 75+ nationalities, English as the company language, and work permit support. Find out more about international applications here.
- Career growth: We believe in continuous learning and proactive career development. Take on challenging work that stretches your abilities, attend trainings, and use new technologies to make a lasting impact.
- Stay healthy: Subsidized canteen, well-being programs, check-ups, and sport allowances.
- Save money: Discounts, exclusive banking terms, and a heavily subsidized public transport pass.
- Family support: Child allowances, gender-neutral parental leave, bilingual company kindergarten, and holiday childcare.
- Competitive salary: Starting at EUR 67.400 gross p.a. including overtime, with market-compliant overpayment based on experience and qualifications. We are happy to discuss your actual salary in person.
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