26 AI Engineer jobs in Austria available for remote work from home. Apply for positions such as Generative AI Engineer (all Genders) for Vienna, Product Engineer - AI Finance, Product Engineer - AI Investing and more! Discover the best work-from-home or hybrid, full- and part-time jobs.
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You will design and develop production-grade multi-agent systems on Google Cloud using advanced foundation models like Gemini and Claude. Your role involves orchestrating agent communication, implementing RAG pipelines, and ensuring robust system performance through monitoring and evaluation.
Own product areas across financial services including insurance, payments, and savings while defining user problems and roadmaps. Collaborate with engineering, design, and operations teams to launch features and iterate based on data and user feedback.
You will own product areas within the AI Investing team, defining user problems, roadmaps, and success metrics. You will collaborate with engineering, design, and operations teams to launch features and drive continuous product improvements.
You will own product areas across financial services like insurance, payments, and savings while defining product direction and success metrics. You will collaborate with engineering, design, and operations teams to launch features and iterate based on user feedback and data.
You will own product areas within the AI Stockbroking division, defining user problems, success metrics, and product roadmaps. You will collaborate with engineering, design, and business teams to launch features and iterate based on data and user feedback.
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You will own product areas within the AI Stockbroking division, defining user problems, roadmaps, and success metrics. You will collaborate with engineering, design, and operations teams to launch features and iterate based on data and user feedback.
You will own product areas within AI Finance, defining user problems, roadmaps, and launch plans while collaborating with engineering and design teams. You are responsible for turning complex financial products into simple customer journeys and driving continuous product iterations based on data and feedback.
You will own product areas across financial services, defining user problems, roadmaps, and success metrics. You will collaborate with engineering, design, and operations teams to launch features and drive iterative improvements based on data and user feedback.
You will own product areas within the AI Neobank, defining product direction, scope, and success metrics while collaborating with engineering and design teams. You are responsible for launching features, monitoring performance, and driving iterative improvements based on user feedback and data.
You will design and implement scalable AWS architectures for data platforms, ML workloads, and generative AI solutions. Additionally, you will act as a trusted technical advisor to clients, supporting pre-sales activities and mentoring junior team members.
Build and ship mobile features for KIRA's AI Finance Agent across Android and iOS platforms. Collaborate with product and design teams to create intuitive flows for insurance, payments, and financial services while improving app performance and reliability.
Build and ship native Android features for an AI Neobank app using Kotlin and Jetpack Compose. Collaborate with product and design teams to optimize user journeys and improve app performance and reliability.
Build and ship native Android features for an AI Neobank app using Kotlin and Jetpack Compose. Focus on optimizing app performance, integrating backend APIs, and creating seamless user flows for financial services.
Build and ship Android features for an AI Neobank app, focusing on clean mobile flows for financial services. The role involves integrating backend APIs and optimizing app performance, responsiveness, and memory usage.
Build and ship native Android features for an AI Finance Agent using Kotlin and Jetpack Compose. Collaborate with product and design teams to simplify complex financial user journeys and optimize app performance.
Build AI-native systems, agents, and automated workflows to improve financial services and internal operations for a Neobank app. Design and productionize scalable AI integrations with LLMs, internal data, and business systems while ensuring reliability and safety.
Build AI-native systems, agents, and automated workflows to optimize financial services and internal operations. Design and productionize scalable AI integrations with LLMs and internal data to reduce manual work.
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Build AI-native systems and agents to automate financial workflows and improve product intelligence for a Neobank app. Design and implement reliable, scalable AI tools focusing on accuracy, latency, and security in a production environment.
Build AI-native systems, agents, and automated workflows to optimize financial services and internal operations. Design and productionize scalable integrations between LLMs, internal data, and business systems.
Evaluate and analyze LLM performance while architecting and building inference and training pipelines. You will contribute to hands-on design, model training, and deployment strategies within a technical greenfield project.
You will design, build, and validate rigorous multilingual benchmarks for large language models within terminal-based workflows. This involves creating realistic task environments, writing deterministic verifier scripts, and participating in a multi-layer quality control process.
You will design and deploy AI-powered customer workflows while collaborating with internal teams to build integrations and automate processes. Additionally, you will troubleshoot production environments and translate customer feedback into actionable product improvements.
Build and operate the AI editing serving stack, focusing on capabilities like inpainting, outpainting, and background removal. You will productionise research models into scalable, cost-aware backend services and mentor other engineers on backend craft.
Build and operate the AI editing serving stack, focusing on capabilities like inpainting, outpainting, and background removal. You will productionise research models into scalable, cost-aware capabilities and lead technical backend initiatives.
The role involves owning and evolving backend services, including crawlers and APIs, while designing systems for scale and reliability. The engineer will build AI pipelines using LLMs to transform real-world data into structured insights.
Design physical objects for 3D printing using open-source CAD software while having your workflow captured to train AI models. Write and execute Python validation scripts to support your engineering design tasks.
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