Top Artificial Intelligence Jobs in Munich

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 design, deployment, and operation of high-performance AI GPU fabrics and datacenter networking (RoCE, RDMA, BGP/ECMP, EVPN/VXLAN). Provide staff-level architecture, cross-team technical leadership, incident escalation, automation (Python/Bash), and operational standards for global datacenter and edge deployments, including inter-datacenter transport and security.

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.

Design, build, and operate the AI storage layer for GPU-heavy edge and core deployments. Architect and optimize storage for distributed training and inference, integrate storage with Kubernetes (CSI), tune performance (RDMA, NVMe-oF, GPU Direct Storage), lead reliability and operational practices, and provide staff-level architectural ownership and cross-team influence while executing hands-on storage engineering.

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.

Provide technical support for ClickHouse and Langfuse customers across EMEA and global regions through cases, chat, Slack, community channels, and calls. Troubleshoot database, cloud infrastructure, AI application, tracing, and evaluation issues within SLA and on-call rotations. Develop documentation and educational content, assist with technical proofs of concept, mentor colleagues, escalate bugs, collaborate with Engineering and Product teams, and support customer implementations directly in codebases.

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.

Lead and run the enterprise AI orchestration platform: own roadmap and budget, manage AI product delivery and vendors, ensure governance and compliance (EU AI Act, GDPR), drive adoption and change management, and provide technical architecture oversight for LLM integrations and agent frameworks.

Drive solution sales for Microsoft Cloud and AI within Automotive and Manufacturing enterprise accounts. Qualify opportunities, build stakeholder relationships, orchestrate deals with partners and consulting teams, align AI/cloud strategies to business outcomes, use analytics to prioritize pipeline, and support secure AI transformation and customer success.

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.

Lead end-to-end AI agent product development for Sales and Marketing: define roadmap, own backlog, drive discovery-to-adoption, lead engineers, partner with UX, and ensure secure, scalable production deployments.

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.