Senior Data Scientist/ML Engineer/AI Engineer (f/m/x)

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.

If you have questions regarding our application process, feel free to check out our FAQ or our page for international applicants.

Your contact:

Alice Sulzer

Talent Acquisition Team