Requirements

Expected technologies

SQL

Python

Node.js

Django

Our requirements

• Master degree in Computer Science, Engineering, or similar.
• 5+ years' working experience in the field of cloud native application architecture (Azure), concepts like microservices, containerization/dockers, serverless compute and event driven architecture, API first and service mesh architectures, particularly experience with in AI or GenAI domain and preferably in the area of M&S & CPG industry. Experience in classical Data & Analytics is a plus.
• Proficient knowledge of Azure Data & AI application development technology stack: Databricks, Azure ML, AI Foundry, Azure Container Services, Azure SQL, Azure Data Lake / Azure Blob, Azure functions, as well as good understanding of frameworks/components used for application development in Python (e.g. Django, Flask, FastAPI), Dash or Node.js.
• Knowhow about RAG (Vector DBs like Prostgres, frameworks like LamaIndex), agentic AI frameworks (e.g., LangChain/LangGraph, N8N) and agent communication (e.g. MCP).
• Profound understanding of data management practices, including data preprocessing. Basic understanding of AI techniques like feature engineering & model training, and different type of DS problems/solutions (LLMs, forecasting mode, optimization model etc.) is a plus.
• Good knowledge of the GitHub ecosystem including the core VCS, GitHub Actions for CI/CD and working with tickets/issues and pull requests. Basic understanding of ML/Ops practices.
• Problem solving and analytical skills, combined with impeccable business judgement. Interpersonal and communication skills, active listening, consulting, challenging, presentation skills.
• Fluent in English, both written & spoken, intercultural awareness and willingness to travel.

Your responsibilities

• Work closely with data scientists, full stack engineers, data architects, and product managers to define project scope and deliverables.
• Assess and translate functional and non-functional requirements into technical concepts in alignment with business objectives and user needs considering robustness, scalability, re-usability, cost efficiency, performance & security & data privacy requirements.
• Together with the data science team, assess and recommend reusable components such as appropriate AI technologies, frameworks, and tools that meet requirements, e.g. RAG, Agent layer, authorization concepts, parsers, UI components etc.
• Stay updated with the latest trends and advancements in AI technology.
• Collaborate closely with the cloud platform team to continuously enhance the AI technology stack of our global cloud-based data, analytics and AI platform.
• Support prototypes and proof-of-concept applications with architecture concepts and validate design concepts and technologies.
• Produce comprehensive documentation, including architectural diagrams, design specifications, and user manuals.
• Together with the product owner steer external providers or internal developers, guide them as architect, provide cost and time estimations, challenge vendor costs and assure quality delivery of vendor implementations & proper handover to support.