• Build and maintain scalable data pipelines using Databricks and Azure Data Lake Storage Gen2 (ADLS Gen2), ensuring reliability and performance across all pipeline stages. • Implement the Medallion Architecture (Raw → Silver → Gold layers) to clean, normalise, and structure technical documentation for downstream AI consumption. • Design and develop the Reasoning Layer using frameworks such as LangChain or LlamaIndex to manage LLM logic, prompt routing, and tool orchestration. • Manage and tune Vector Databases (e.g. Pinecone, Weaviate, or Azure AI Search) to enable fast and accurate semantic retrieval across the corporate knowledge base. • Develop Azure Apps and Azure Functions to connect the AI system to external enterprise platforms such as Salesforce and SharePoint, enabling end-to-end automation.

Role Description Are you passionate about data engineering and ready to revolutionize how data is managed and utilized within an organization? We are looking for a skilled and innovative Analytics Engineer to join our dynamic team and help us implement a cutting-edge Data Mesh architecture. Your daily adventures will include: - Collaborate with cross-functional teams including data analysts, data scientists, and software engineers to understand data requirements and design optimal data solutions in the Data Mesh environment. - Develop, implement, and maintain scalable data products that enable the seamless flow of data from various sources to the Data Mesh architecture. - Create and manage data models that cater to the specific needs of data consumers while adhering to data governance and security standards. - Design and build data quality monitoring frameworks to ensure data accuracy, consistency, and reliability. - Stay updated with the latest industry trends and best practices in Data Engineering and Data Mesh to continuously improve data pipelines and processes. - Build high-performance APIs to access and query data from the data warehouse. - Perform data analysis required to troubleshoot data-related issues and assist in the resolution of data issues. - Coordinate and oversee the successful delivery of complex data engineering projects, ensuring alignment with timelines, objectives, and stakeholders. Qualifications - You have advanced knowledge of at least one programming language and are happy to learn more. Our core languages are Scala and Python. - Expert level of SQL (especially SparkSQL) and Data Warehouse concepts, Database. Experience in building data pipelines is a core requirement. - Love getting your hands dirty with the data implementing custom ETLs to craft it into information. - You have knowledge of distributed systems, Lambda, AWS S3, AWS CloudWatch. - Experience with AWS, Hive, Spark, Trino, Databricks is helpful. - Enjoy working with stream processing frameworks like Spark structured streaming, Kafka streams. - You understand requirements beyond the written word. Your attention to detail leads to a delightful user experience. - Fluent proficiency in Business English. - Exceptional analytical skills, lateral thinking, and experience in solving challenging problems. - Experience working with Data Visualization tools (e.g., Tableau, Metabase) is a plus. Requirements - Advanced knowledge of programming languages (Scala, Python). - Expert level SQL skills (especially SparkSQL). - Experience in building data pipelines. - Knowledge of distributed systems and AWS services. - Experience with stream processing frameworks. - Fluent in Business English. - Exceptional analytical and problem-solving skills. Benefits - Flexible location: Hamburg, Berlin, Barcelona, or Athens. - Work in a multinational, diverse, highly motivated, and collaborative team. - Opportunity to work with cutting-edge technology. - Focus on data-driven decisions that drive business forward.

• AI Feature Development: Design, build, and deploy production-grade AI capabilities into our SaaS product, utilizing RAG pipelines, autonomous agentic tools, and Model Context Protocol (MCP). • Architectural Engineering: Architect and maintain highly scalable, reliable backend solutions using ASP.NET Core and F#, strictly adhering to functional programming principles and event-driven architectures. • Vector & Data Management: Implement and optimize vector databases to ensure ultra-low latency, highly accurate semantic search and contextual data retrieval. • Model Selection & Evaluation: Evaluate, benchmark, and integrate diverse LLMs and foundation models, matching their unique capabilities to specific product requirements for optimal cost, speed, and accuracy. • Cloud & AI Infrastructure: Orchestrate and manage secure, scalable workloads within the Azure ecosystem, specifically leveraging Azure AI deployments.

Role Description We're building a program for experienced engineers transitioning into system architecture roles. We need AI Systems Engineering practitioners who can do more than just know their craft — they need to help build the curriculum and turn their expertise into content others can learn from. This is a content authoring role. You'll start by shaping the program syllabus based on our existing draft, then move into producing lessons using AI-gen tools — following our content guidelines, reviewing the output, and fine-tuning it until it's accurate and teachable. An LX designer will review your content and send comments back; you'll iterate from there. The best candidates are people who are opinionated about what good systems engineering looks like and what engineers need to learn, can spot when something is oversimplified or wrong, and are comfortable working in a structured production process and keeping up with deadlines. Your audience: experienced engineers looking to level up to system architecture roles. They will spot shallow content instantly. Format: async-first, project-based, estimated 4-6 months. We expect you to be ready to commit from 20 to 40 hrs/week. Please submit all resumes or CV's in English. What you will do - Review and shape the existing syllabus draft — validate topic sequencing, flag gaps or unrealistic scope, and make sure the content reflects how these systems are actually built in production. - Define clear learning objectives per topic: what should a student be able to do after this lesson, not just know. - Produce lessons using AI-gen tools following our content guidelines — then review, fact-check, and fine-tune the output until it's technically sound. - Design hands-on projects and exercises that are realistic for a working engineer studying 20 hrs/week. - Write supporting content: project instructions, rubrics, and reviewer guides. - Respond to LX designer feedback and iterate on content — this is a back-and-forth process, not a one-time handoff. Qualifications - 5+ years of real-world experience as a Senior Systems Engineer with depth in your area. - Has designed and shipped systems at scale in a real company — not just coursework or side projects. - Can explain why a decision was made, not just how it was implemented. - Strong technical communication skills — ability to explain complex topics clearly to learners. - Comfortable using AI tools for content drafting and iteration. - Strong English C1+ — content will be in English for a US-based audience. - Attention to detail, proactivity and ability to meet deadlines independently. Benefits - Milestone-based payments tied to deliverables. - Fully remote work with flexible hours. - A digital office — we use modern tools (Notion, Miro, Slack, Figma) to keep collaboration smooth. - Professional trust and autonomy — no micromanaging. - The chance to see real impact: our metric is graduates landing jobs in tech. - Join a diverse, international, and close-knit team excited to work with you.