Senior Data Scientist/ML Engineer/AI Engineer (Vienna)

What you can expect
• End-to-end ownership of ML, AI and agentic AI use cases: problem framing, data
preparation, modelling, orchestration, evaluation, and deployment to production.
• Design agent architectures (planner–executor, multi-agent collaboration) with
memory, reflection, and tool-use; ensure robustness, transparency, and
controllability.
• Implement MCP (Model Context Protocol) for standardized, secure tool
integrations and capability discovery across internal and external services.
• Orchestrate LLMs and tools using agent frameworks (e.g., LangChain, LlamaIndex,
Semantic Kernel, OpenAI Assistants), including function/tool calling, fallbacks, and
guardrails.
• Build and optimize RAG pipelines: ingestion, chunking, embeddings, vector stores,
retrieval strategies, caching, and evaluation for precision/recall and latency.
• Establish strong LLMOps/MLOps practices: experiment tracking, prompt/dataset
versioning, CI/CD, model/artefact registry, monitoring, and incident response.
• Drive reliability, safety, and compliance: prompt-injection defenses, content
filtering, policy enforcement, red-teaming, and measurable quality gates.

• Conduct rigorous offline/online evaluation: backtesting, time-series cross-
validation, A/B and shadow deployments, canary releases, drift and impact monitoring.
• Optimize performance and cost (latency, throughput, rate limits, batching,
streaming, caching); maintain usage and cost dashboards.
• Collaborate with product owners, engineers, and business stakeholders; deliver
scalable solutions on Databricks (AWS) and integrate with bank systems.
• Produce clear documentation, reusable templates, and playbooks; mentor
teammates and contribute to community best practices.

What you bring to the table
• 3+ years professional experience in developing and operating software solutions.
• You are a versatile team player that enjoys collaboration but also solves problems on its own
• 2+ years professional experience (hands-on) with cloud computing with AWS (AWSLINUX and AWS
Lambda)
• 2+ years professional experience (hands-on) with various Database technologies and ideally Data
Lake (AWS/S3)
• 2+ years professional experience working in a product-driven environment
• Programming skills, Phyton experience (ideally Django) and experienced in scripting RESTful AP
• You demonstrated ability to build processes that support data transformation, data structures,
metadata, dependency and workload management.
• You have basic knowhow with ETL tools
• You are familiar with agile working methods

Soft skills

• Proactivity; Curiosity; Responsibility; Ideas & Confidence.
• Structured working approach and problem-solving skills.
• Fluent English; German or another CEE language is appreciated, but not mandatory.