Top Artificial Intelligence Jobs in Munich

Lead research and development of AI accelerator/NPU IPs for embedded products. Architect RTL and hardware to meet power/performance/area targets, collaborate with compiler and software teams, model systems, and mentor cross-functional teams toward chip tape-out.

Develop and benchmark 3D computer vision and localisation systems (SLAM, visual odometry, scene matching, geo-registration, 3D reconstruction). Extend geometric deep learning and feature-matching methods, design experiments and benchmarks, adapt models to hardware constraints, and collaborate with research, engineering, and product teams to deploy robust AI solutions.

Lead product direction, roadmaps, priorities, standards, and success metrics for major AI neobank areas. Guide PMs, product owners, designers, and engineers across multiple squads while balancing user experience, data, engineering, regulatory, operational, and business constraints. Drive launch quality, post-launch learning, continuous improvement, and a high-performing product culture across financial services including insurance, payments, savings, investing, and travel.

Lead product direction, roadmaps, standards, metrics, execution, and quality for major areas of KIRA’s AI Neobank App. Guide PMs, product owners, designers, and engineers across multiple squads and financial services, including insurance, payments, savings, investing, and travel. Translate regulatory and business constraints into product decisions, drive launches and iteration, and promote a fast, user-focused product culture.

Leads major product areas for KIRA’s AI Finance App, owning product direction, roadmaps, standards, metrics, execution, launch quality, and continuous improvement across multiple squads. The role involves guiding PMs, product owners, designers, and engineers while balancing UX, data, engineering, regulatory, operational, and business constraints across insurance, payments, savings, investing, and travel products.

The AI Engineer will build data pipelines and improve ML systems for reliability in production. Responsibilities include schema design, data infrastructure, and model evaluation, ensuring high-quality outputs and integration with product workflows.

Build and deploy production-grade LLM capabilities for the Kayzen Console. Responsibilities include developing AI-backed APIs and full-stack features, implementing RAG, embeddings, agents, and tool calling, and establishing evaluation, monitoring, observability, and feedback systems. The role optimizes quality, latency, reliability, and cost; troubleshoots production issues; collaborates with Product, ML, and Engineering; and turns prototypes into maintainable AI products.

Own product areas for KIRA’s AI neobank across insurance, payments, savings, investing, travel, and other 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 workflows; and use research, feedback, experiments, and performance data to drive post-launch improvements.

Own AI Investing product areas across financial services, defining user problems, product scope, metrics, roadmaps, and launch plans. Partner with engineering, design, data, operations, compliance, and business teams to simplify complex financial journeys. Use research, feedback, metrics, experiments, and production insights to make decisions, launch features, monitor performance, and drive continuous improvements while balancing speed, experience, business impact, compliance, and operational complexity.

Leads global privacy and AI legal matters for a SaaS employment platform. Advises Product, Engineering, Security, and business teams on privacy by design, AI governance, data protection, workforce data, incidents, regulatory compliance, vendor reviews, transfers, and contract terms. Builds scalable policies, controls, templates, training, and customer-facing trust materials while monitoring global privacy and AI regulations.

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

Own product areas within AI Stockbroking and other financial services. Define user problems, product direction, scope, metrics, roadmaps, and launch plans. Collaborate with engineering, design, data, operations, compliance, and business teams to simplify complex financial products, launch features, monitor performance, and iterate using data, feedback, research, and production insights. The role requires strong product judgment, execution, prioritization, stakeholder management, and ownership.

Own AI Finance product areas across insurance, payments, savings, investing, travel, and other financial services. Define user problems, product strategy, roadmaps, success metrics, and launch plans; collaborate with engineering, design, data, operations, compliance, and business teams; simplify complex financial journeys; and use data, feedback, research, and production insights to iterate and improve products.

Own product areas for an AI neobank across insurance, payments, savings, investing, travel, and other financial services. Define product direction, user problems, scope, metrics, roadmaps, and launch plans. Collaborate with engineering, design, data, operations, compliance, and business teams to simplify financial products, launch features, monitor performance, and iterate based on data, feedback, research, and production issues.

Own AI Finance product areas across insurance, payments, savings, investing, travel, and related services. Define user problems, product scope, metrics, roadmaps, and launches; collaborate with engineering, design, data, compliance, operations, and business teams. Simplify complex financial workflows, use research and performance data to guide decisions, launch quickly, and iterate based on feedback and results.

Own product areas within KIRA’s AI Neobank across financial services such as 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 data, research, feedback, and production insights to launch, measure, and continuously improve products.

Own AI Finance product areas across insurance, payments, savings, investing, travel, and related financial services. 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, monitor performance, and iterate using data, research, feedback, and production insights.

Own product areas for KIRA’s AI Stockbroking and broader 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 products. Use research, feedback, experiments, and performance data to launch, monitor, and iteratively improve products while balancing speed, user experience, business impact, compliance, and operational complexity.

Own product areas within AI Investing and other financial services. Define user problems, product scope, success metrics, roadmaps, and launch plans; collaborate with engineering, design, data, compliance, operations, and business teams; simplify complex financial products; launch features; monitor performance; and iterate using data, research, feedback, and production insights.

Own AI Finance product areas across insurance, payments, savings, investing, and travel. Define user problems, roadmaps, success metrics, and launch plans; collaborate with engineering, design, data, operations, compliance, and business teams; simplify financial journeys; launch features; monitor performance; and iterate using data, feedback, research, and production insights.

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.