Industry: Artificial Intelligence & ML

Location: Vienna Hybrid

Capacity: Full-time

Duration: Long-term

Language: English

These are your responsibilities:

• End-to-end responsibility for ML, AI, and agent-based AI use cases: from problem definition to data preparation, modeling, orchestration, evaluation, and production deployment.
• Design of agent architectures (e.g., planner–executor, multi-agent collaboration) with features like memory, reflection, and tool use, taking into account robustness, transparency, and controllability.
• Implementation of the Model Context Protocol (MCP) for standardized and secure tool integration as well as capability detection across internal and external services.
• Orchestration of LLMs and tools using agent frameworks (e.g., LangChain, LlamaIndex, Semantic Kernel, OpenAI Assistants), including function/tool calls, fallbacks, and guardrails.
• Development and optimization of RAG pipelines (Retrieval-Augmented Generation): data ingestion, chunking, embedding, vector storage, retrieval strategies, caching, and evaluation in terms of precision, recall, and latency.
• Establishment of robust LLMOps/MLOps practices: experiment tracking, prompt and data versioning, CI/CD, model and artifact management, monitoring, and incident response.
• Promotion of reliability, security, and compliance: protection against prompt injection, content filtering, policy enforcement, red-teaming, and measurable quality controls.
• Conducting rigorous offline/online evaluations: backtesting, time series cross-validation, A/B and shadow deployments, canary releases, drift and impact monitoring.
• Optimization of performance and cost: latency, throughput, rate limits, batching, streaming, caching, and development of monitoring dashboards for usage and cost.
• Close collaboration with product owners, engineers, and business stakeholders; implementation of scalable solutions on Databricks (AWS) and integration into banking systems.
• Creation of clear documentation, templates, and playbooks; mentoring of colleagues and contribution to best practices in the community.

You bring:

• 3+ years of professional experience in developing and operating software solutions.
• You are a team player, enjoy collaborative work, but are also capable of solving problems independently.
• 2+ years of hands-on experience with cloud computing on AWS, especially with AWS Linux and AWS Lambda.
• 2+ years of experience working with various database technologies and ideally with data lakes (e.g., AWS S3).
• 2+ years of experience in a product-driven environment.
• Programming skills in Python (ideally with Django) and experience in building RESTful APIs.
• Proven experience in setting up processes for data transformation, data structuring, metadata management, and workload management.
• Basic knowledge of ETL tools.
• Familiarity with agile working methods.

Soft skills:

• Initiative, curiosity, sense of responsibility as well as creative ideas & self-confidence.
• Structured approach to work and strong problem-solving skills.
• Fluent English spoken and written; German or another CEE language is a plus, but not required.

JobNr: 3379