Working Student AI Solutions Architect – Generative AI & Data Platforms
Part-time working-student role at a Hamburg-based data & AI engineering consultancy: turning client business requirements into solution architectures for data platforms and generative-AI systems (RAG, agents) on AWS, Snowflake, Databricks or GCP, prototyping with Python and SQL alongside founders and engineers.
- Compensation
- Not disclosed
- Location
- Berlin, Germany
- Work setup
- Not specified
- Seniority
- Not specified
- Employment
- Internship
- Experience
- Not specified
- Category
- Ai engineering
- Posted
Skills
Must have
- Current university enrollment in a relevant technical discipline
- Substantial hands-on experience building software or data systems
- Evidence of delivered systems used by others; ability to explain design choices, implementation and operational lessons
- Strong Python and SQL skills
- Practical cloud experience
- Understanding of APIs, data modeling and deployment
- Applied understanding of large language models, RAG and the data foundations these systems require
- Judgement to own a defined workstream, surface risks early and communicate technical decisions clearly in English
Nice to have
- Experience with Amazon Bedrock, Anthropic Claude, Terraform, Lakehouse architecture or technical discovery with business stakeholders
Full description
IMPORTANT Application note
Please apply only through this job portal. Kindly do not send applications or recruitment messages by email or LinkedIn. Only applications submitted through the portal will be considered. Thank you.
About AgentixLake
AgentixLake GmbH is a Data and AI engineering consultancy based in Hamburg, Germany. We design, build and operate production-grade data platforms and AI systems in our customers’ cloud accounts or on-premises environments. We are an AWS Services Partner and a Certified Services Partner in Anthropic’s Claude Partner Network. Our commercial focus is DACH and the Gulf region, alongside selected international opportunities.
Your role
Design the path from a business requirement to a working data and AI system. You will work directly with our founders and engineers to turn discovery findings into architecture decisions, implementation plans and tested components.
Our architecture and advisory work connects enterprise data platforms with generative AI, AI agents and business applications. Depending on the engagement, solutions run on AWS, Snowflake, Databricks, Google Cloud or customer-managed infrastructure.
What you will do
Translate business workflows, existing systems and data constraints into clear solution designs, with explicit assumptions and acceptance criteria.
Design data flows connecting ingestion, storage, retrieval, model inference, APIs and downstream enterprise systems.
Evaluate trade-offs across cloud services, open-source components and on-premises deployment, including security, reliability, cost and maintainability.
Create architecture diagrams, technical decision records and delivery estimates; contribute to discovery workshops and design reviews.
Validate important assumptions with Python, SQL, API integrations or infrastructure prototypes, then work with engineers on implementation.
Specify access controls, evaluation, observability and human approval steps for enterprise RAG and agentic workflows.
What you bring
Current university enrollment in a relevant technical discipline, combined with substantial hands-on experience building software or data systems.
Evidence that you have delivered systems used by others and can explain your own design choices, implementation and operational lessons.
Strong Python and SQL skills, practical cloud experience and an understanding of APIs, data modeling and deployment.
Applied understanding of large language models, retrieval-augmented generation and the data foundations these systems require.
The judgement to own a defined workstream, surface risks early and communicate technical decisions clearly in English.