Werkstudent (m/w/d) Software Development & AI
Develop modern Java applications and integrate AI technologies such as OpenAI and Claude APIs. Research and build prototypes for RAG systems using current AI development tools.
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Develop modern Java applications and integrate AI technologies such as OpenAI and Claude APIs. Research and build prototypes for RAG systems using current AI development tools.
Develop and implement AI solutions by designing proof-of-concepts and translating them into minimum viable products. Collaborate with cross-functional teams to optimize AI models and integrate capabilities into existing systems.
Lead the design and delivery of enterprise-grade Generative AI solutions, including RAG pipelines and multi-modal AI systems. Define the technical roadmap for AI initiatives and guide cross-functional teams to implement scalable, secure, and compliant AI architectures.
Lead technical pre-sales discussions to translate customer challenges into end-to-end agentic AI solutions using the NVIDIA AI Enterprise platform. Act as the primary technical author for proposals and SOWs while presenting architectural designs to C-level executives.
Contribute to innovation-driven projects by designing scalable, business-ready apps and solutions using SAP and AI technologies. Collaborate with cross-functional teams to turn ideas into real-world solutions for live client environments.
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Design, build, and deploy production-ready AI agents that automate end-to-end business tasks and workflows. Partner with business leaders to translate complex SOPs and decision logic into scalable, secure AI-driven solutions.
The AI Product Manager will oversee the development and delivery of GenAI-powered products, managing the product backlog and aligning development with business objectives. They will lead agile ceremonies and collaborate with cross-functional teams including engineering, data science, and UX/UI.
Develop scalable, production-ready AI-powered features across the full stack from UI to deployment. Collaborate with product owners to design AI workflows and optimize system performance, latency, and cost.
Provide native-level Māori language vetting, QA, and data annotation to ensure AI outputs are natural and culturally accurate. Develop educational resources and feedback documentation to improve AI alignment with campaign expectations.
Provide native-level Taiwanese linguistic vetting and quality assurance for AI data projects. Develop educational resources and feedback documentation to improve AI alignment and cultural accuracy.
Design and implement backend systems for agentic workflows, including orchestration layers and multimodal systems. Develop GraphRAG-based knowledge retrieval and optimize the performance and cost of multi-agent pipelines.
Lead the strategic design and deployment of AI-driven solutions, including LLMs and automation frameworks, to enhance operational efficiency. Manage the end-to-end AI lifecycle and build a high-performing team of researchers and engineers.
Define and scale a relationship-first AI character platform that drives measurable business outcomes for brands and studios. Lead the product strategy, roadmap, and the transition from bespoke deployments to a scalable B2B platform.
Own major consumer surfaces and customer journeys end-to-end, setting the one-year strategy and quality bar. Act as a peer-builder using AI-native workflows to create prototypes and drive business impact.
Act as a technical ambassador and advisor to C-level executives, bridging the gap between engineering innovation and enterprise business needs. Lead the design of large-scale AI and data architectures while providing strategic feedback to the product team.
Facilitate weekly live Zoom sessions to help non-technical professionals apply AI for data analysis through hands-on projects. Responsibilities include customizing course materials, providing guidance via Slack, and supporting learners in building reusable AI-powered decision-making workflows.
The Senior BI Analyst partners with AI Evaluation & Monitoring teams to collect, clean, and interpret data sets to support data-driven decisions. They are responsible for running validation studies, instrumenting production monitoring, and translating complex analyses into actionable insights for non-technical stakeholders.
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The Senior BI Analyst partners with AI Evaluation & Monitoring teams to collect, clean, and interpret data to drive data-driven decisions. They are responsible for executing validation studies, monitoring production AI performance, and mentoring junior developers.
Develop impactful software by translating user and customer problems into clean technical solutions. Integrate AI coding tools like Cursor and Claude Code into the daily development workflow to optimize business processes.
Lead the development and delivery of production-grade, reusable AI starter kits and reference architectures across various business units. Drive engineering excellence by implementing AI-SDLC practices, ensuring reliability, security, and scalable deployment of LLM application layers.
Lead the design and implementation of production-grade, reusable AI starter kits and reference architectures across various business units. Drive engineering excellence by establishing CI/CD patterns, ensuring system reliability, and mentoring junior engineers on AI-driven development lifecycles.
Lead the strategy and roadmap for the Accounts and Tooling portfolio, focusing on creating scalable AI-powered user experiences. Use AI tools and prototypes to rapidly validate ideas and move from customer insights to production-grade solutions.
Generate collision-accurate 3D meshes from 2D images and write procedural generation scripts using Python or JavaScript. Deliver structured programmatic outputs and maintain detailed trajectory logs to train AI systems on geometric construction.
Develop pipelines to extract complex data from visual documents using Vision-Language Models and layout analysis. Orchestrate AI agents and chains using LangChain or LangGraph to reason about data and generate accurate responses.
Architect and develop robust ETL pipelines for graph ingestion and manage high-volume data streams using Kafka. Ensure graph hygiene through automated deduplication and optimize query performance for large-scale datasets.
Design and build server-side APIs and support tooling to manage large-scale data operations and backups. Utilize AI-assisted development tools to accelerate implementation while ensuring security, performance, and correctness.
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The Delivery Lead manages the end-to-end execution of enterprise AI engagements, ensuring milestones are met on time and within budget. They serve as the primary escalation point for clients and coordinate between GMs, Product Managers, and Technical Leads to ensure successful adoption.
Drive adoption and growth for SMB and Mid-Market customers by managing renewal cycles and identifying expansion opportunities. Partner with technical teams to ensure smooth implementation and run workshops to demonstrate product value.
Build and manage a long-term investment fund focused on resilience against AI disruption and structural economic shifts. Lead capital raising efforts by sourcing and closing LP relationships while executing investments across various asset classes.
Lead the discovery and rapid prototyping of AI solutions, ranging from rule-based systems to LLM-based agentic workflows. Collaborate with business stakeholders to define problem statements and provide technical handoffs to the AI Engineering team for production.
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