Top Artificial Intelligence Jobs in Munich

Own product areas across AI investing and financial services, defining user problems, product scope, metrics, roadmaps, and launch plans. Collaborate with engineering, design, data, operations, compliance, and business teams to simplify complex financial workflows. Use research, feedback, experiments, metrics, and production insights to guide decisions, launch features, monitor performance, and drive ongoing iterations while balancing speed, customer experience, business impact, compliance, and operational complexity.

Own product areas within AI investing and broader financial services, defining user problems, product scope, success metrics, roadmaps, and launch plans. Collaborate with engineering, design, data, operations, compliance, and business teams to simplify complex financial journeys. Use metrics, research, feedback, and production issues to guide decisions, launch features, monitor performance, and drive iterative improvements while balancing speed, user experience, business impact, compliance, and operational complexity.

Develop and deploy AI-powered capabilities across product and business teams. Act as a forward-deployed engineer, embedding with finance, sales, marketing, and product teams to introduce agentic methodologies, support AI adoption, shape the company platform and strategy, and translate learnings into scalable solutions. The role emphasizes production-quality code, business impact, adaptability, collaboration, and effective work in a global distributed environment.

Own product areas within AI Finance across insurance, payments, savings, investing, travel, and related financial services. Define user problems, product direction, scope, metrics, roadmaps, and launches. Collaborate with engineering, design, data, operations, compliance, and business teams to simplify financial products, launch features, monitor performance, and iterate using data, research, feedback, and production insights. The role is remote but requires candidates to be based in Germany and communicate strongly in English.

Own product areas within AI stockbroking and broader financial services. Define user problems, product scope, metrics, roadmaps, and launch plans; collaborate with engineering, design, data, operations, compliance, and business teams. Simplify complex financial products, use research and performance data to guide decisions, launch features, monitor results, and drive continuous iteration while balancing speed, user experience, business impact, compliance, and operational complexity.

Build and ship full-stack features for a data intelligence SaaS platform, spanning backend services and frontend interfaces. Use AI coding assistants to accelerate development while applying sound engineering judgment. Participate in architecture discussions, code reviews, testing, incident response, troubleshooting, documentation, and knowledge sharing. Partner with product managers to translate requirements into technical solutions. The role emphasizes SaaS architecture, AWS cloud fundamentals, Docker, Kubernetes, CI/CD, agile delivery, autonomy, and production ownership.

Own AI Investing product areas across financial services by defining user problems, product scope, metrics, roadmaps, and launches. Partner with engineering, design, data, operations, compliance, and business teams to simplify complex financial workflows. Use research, feedback, experiments, and performance data to iterate quickly, balance user experience and business impact, and drive execution with high ownership.

Own product areas within an AI neobank across financial services such as insurance, payments, savings, investing, and travel. Define user problems, scope, metrics, roadmaps, and launch plans; collaborate with engineering, design, data, operations, compliance, and business teams; simplify complex financial journeys; use research, feedback, experiments, and performance data to improve products; and balance speed, usability, business impact, compliance, and operational complexity.

Own product areas within BJAK’s AI Neobank across financial services such as payments, savings, investing, insurance, and travel. Define user problems, product direction, metrics, roadmaps, and launches; collaborate with engineering, design, data, operations, compliance, and business teams; and use research, feedback, metrics, and production insights to iterate products and improve customer journeys.

Own product areas for BJAK’s AI Stockbroking and broader financial services offerings. Define user problems, product direction, scope, metrics, roadmaps, and launch plans. Collaborate with engineering, design, data, operations, compliance, and business teams to simplify financial products, launch features, analyze performance, and iterate based on feedback and production insights.

Own AI Investing product areas across financial services, defining user problems, product scope, metrics, roadmaps, and launch plans. Collaborate with engineering, design, data, operations, compliance, and business teams to simplify financial products, ship features quickly, monitor performance, and iterate using data, research, feedback, and production insights.

Own product areas across AI Finance, including insurance, payments, savings, investing, and travel. Define user problems, product scope, metrics, roadmaps, and launch plans; collaborate with engineering, design, data, operations, compliance, and business teams; simplify complex financial workflows; and use research, feedback, experiments, and performance data to iterate after launch.

Own AI Finance product areas across insurance, payments, savings, investing, travel, and other financial services. Define user problems, product direction, scope, metrics, roadmaps, and launches while collaborating with engineering, design, data, compliance, operations, and business teams. Simplify complex financial products, ship quickly, monitor performance, use feedback and experiments, and continuously improve customer experiences while balancing business impact, compliance, and operational complexity.

Develop and optimize GPU- and CPU-accelerated numerical software libraries for AI, analytics, image processing, computer vision, and scientific simulation workflows. Responsibilities include designing scalable algorithms, performance tuning, benchmarking across architectures, collaborating on feature requirements and technical roadmaps, providing technical leadership, and improving library usability and performance.

Designs end-to-end enterprise AI architectures on AWS, including LLM orchestration, integrations, cloud infrastructure, security, scalability, and governance. Leads technical discovery workshops, creates architecture documentation and standards, guides engineering squads, reviews designs, presents decisions to senior stakeholders, and evaluates third-party AI platforms for buy-versus-build decisions. Requires extensive senior architecture experience and fluent Dutch and English.

Own the technical presales strategy for complex enterprise deals across DACH and expansion markets. Lead discovery, technical deep dives, customized demonstrations, solution design, POCs, and POVs. Translate AI Agent and contact center technologies into business value for senior stakeholders, provide competitive analysis, and collaborate with product teams. Represent NiCE Cognigy through events, webinars, trade shows, and thought leadership while supporting internal enablement and customer feedback.

Lead simulation-driven development of power modules using multiphysics (electrical, thermal, mechanical) models, digital twins, AI-augmented optimization, and automation to accelerate SiC/GaN power-electronics design and reliability prediction while collaborating with global teams.

Pre-sales technical architect partnering with sales to design, evaluate, and deploy Claude-based LLM solutions for enterprise customers. Responsibilities include technical discovery, architecture guidance, building evals, integration planning, creating technical content, cross-team coordination, and occasional on-site workshops.

The Sales Development Representative will identify potential manufacturing customers, initiate conversations, qualify leads, and work closely with Account Executives to enhance sales pipeline and strategies.

As a Solutions Engineer, you'll work with enterprise clients, ensuring effective use of ChatGPT and OpenAI APIs to deliver business value by understanding their needs and guiding their AI strategies.

As a Lead/Staff Full Stack Engineer, you'll design and develop full-stack applications and AI agents for the GenAI platform, focusing on rapid deployment and impactful decision-making for various industries. You'll also mentor engineers and lead major projects.

As a Principal Full Stack Engineer, lead the development of the GenAI platform, design full-stack applications, and mentor engineers. Build scalable systems for AI agents affecting key industries, ensuring security and reliability.

The Backend Engineer will develop and maintain features for Restream web services, design backend APIs, ensure infrastructure resilience, and contribute to a collaborative team environment.

Translate TecAlliance business problems into production-ready AI solutions: define use cases, prototype with ML/LLM components, iterate with stakeholders, and hand over to production while documenting and scaling best practices.

Lead MLOps Engineer responsible for building and automating the lifecycle of multimodal agentic AI: orchestration (LangChain/LangGraph), training pipelines for LLMs and CV, containerized model deployment, low-latency inference, model monitoring/drift detection, and optimizing ML infrastructure for performance and cost.