Top Artificial Intelligence Jobs in Munich

Lead Nuitee’s agentic AI strategy and capabilities for searching, booking, paying for, modifying, and canceling hotel stays. The role combines hands-on software engineering, product development, technical leadership, commercial opportunity identification, and team building. Reporting to the CEO, this leader will design secure agent-native APIs and MCP tools, improve transaction reliability, and take new products from concept to production across Nuitee’s travel infrastructure.

Build a model enablement platform for heterogeneous AI computing across AIPUs, CPUs, GPUs, NPUs, and other accelerators. Responsibilities include model ingestion, graph partitioning, compilation, runtime execution, performance profiling, memory and scheduling optimization, large-model offloading, and verification integrated into CI. The role combines architecture ownership with hands-on C++ and Python engineering across model frontends, compilers, runtimes, and application pipelines.

Own LLM and VLM enablement on Axelera AI hardware, from studying and profiling models through productionizing them in the Voyager SDK. Responsibilities include PyTorch references, quantization, weight mapping, model contracts, pipeline integration, KV-cache management, multimodal serving, accuracy validation, and bring-up platform development. The role also shapes GenAI, agent, and speech capabilities for edge devices.

Leads EMEA AI, paid media, digital marketing, website, virtual event, email, and nurture strategies. Manages four direct reports, agencies, budgets, forecasting, campaign planning, AI marketing adoption, localized digital experiences, GEO initiatives, and performance optimization. Partners with global and regional stakeholders to improve engagement, conversion, pipeline contribution, and customer lifecycle outcomes.

Lead the AI architecture for Productboard Insights, designing agent-native systems, context infrastructure, self-healing workflows, evaluation processes, and AI code-review optimization. Own technical direction across Insights, Spark, and platform teams; drive features from concept through beta; optimize quality, latency, cost, and reliability; write production code; and develop engineers through documentation and reviews.

Build and own AI models, data pipelines, evaluation suites, and AI product features for construction procurement software. Develop document extraction and workflow automation using generative AI, LLMs, RAG, and optimization algorithms. Design complex data models, integrations, backend services, and production systems using Go, GraphQL, PostgreSQL, and AWS.

Lead design and build of an end-to-end AI contract-review agent: prompt orchestration, RAG pipelines, fine-tuning, web UI and tooling, data/model infra, deployment (CI/CD/cloud), and product-driven features like assumption mapping and contract diagnostics.

Own Vogel’s AI-first technology architecture, including the data layer above DATEV, agent infrastructure, integrations, observability, evaluation, and control systems. Build production software, establish reproducibility and auditability, hire and lead the initial engineering team, and scale a shared technology base across acquired advisory firms. The role is highly hands-on, requires in-person work in Munich, and offers a path to the full CTO mandate.

Lead a portfolio of complex, high-visibility technical programs for Databricks Professional Services. Responsibilities include aligning programs with customer objectives, coordinating technical milestones and dependencies, driving delivery excellence, leading technical delivery discussions, improving processes, integrating AI tools into workflows, and mentoring junior technical program managers. PMP and Databricks Associate-level certifications are required within six months of hire.

Build and maintain React and TypeScript interfaces for an agentic AI investigation product. Develop workflow editors, investigation timelines, dashboards, and data-heavy tables; maintain Module Federation microfrontends and host contracts; contribute to shadcn/ui and Tailwind design systems; integrate typed FastAPI APIs; and support testing, CI, deployment, and AWS preview environments. Collaborate with Product, UX, backend, and Data Science teams while using AI coding tools.

Drive adoption of Dataleap among existing customers by identifying champions, building AI agents alongside teams, running workshops and enablement sessions, and ensuring customers achieve measurable value. Serve as a trusted customer partner, communicate feedback to product and engineering, and automate internal workflows using Dataleap. The role is based in Munich and requires native German and fluent English.

Drive mid-market sales of Harvey’s AI solutions across DACH. Manage named accounts and the full customer lifecycle, including prospecting, demonstrations, contracting, onboarding, expansion, and renewals. Build executive relationships, conduct consultative sales, meet revenue targets, maintain pipeline and CRM accuracy, and collaborate with product and engineering teams. Help develop sales playbooks and resources. Fluency in English and German is required, with occasional travel to customer and company offices.

Owns post-deployment value realization, adoption, and expansion for strategic Private Cloud AI customers across Central Europe. Provides enterprise AI architecture guidance, leads roadmap and adoption reviews, identifies expansion opportunities, facilitates technical and executive workshops, and builds reusable global playbooks. The role combines deep AI and GenAI expertise with customer-facing technical sales, commercial judgment, account management, and frequent onsite travel.

Drive Azure and AI sales across the DACH market, managing opportunities from qualification through close and building pipeline against Azure consumption, workload adoption, and AI deployment targets. Lead customer conversations, technical sales cycles, workshops, proofs of concept, and solution envisioning. Translate customer challenges into secure Azure architectures, guide responsible AI adoption, and build trusted relationships with senior decision makers while collaborating with account executives, engineers, partners, and customer success teams.

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.

Drive technical sales of Microsoft and GitHub cloud and AI development technologies for manufacturing customers in Germany. Lead workshops, demos, architecture discussions, pilots, and proofs of concept involving GitHub, Copilot, Azure, CI/CD, DevOps, platform engineering, security, and observability. Partner with account teams, engineers, and customers to qualify opportunities, overcome technical barriers, and support adoption across factory, edge, SAP-adjacent, and industrial-data scenarios.

As an AI Automations Engineer, you will design and build tooling for GTM, Operations, and Finance teams, automating processes and enhancing systems with a focus on AI.

Owns full-cycle recruiting for commercial, operational, and technical roles across global markets. Responsibilities include sourcing passive candidates, building pipelines for hard-to-fill positions, advising hiring leaders, coordinating interviews and offers, maintaining accurate Greenhouse data, and improving hiring processes through systems thinking, data, AI, and automation.

Leads strategic AI initiatives from opportunity identification through production deployment and optimization. Bridges business and technical teams, mentors project teams, scales LLM, generative AI, and agentic AI capabilities, and supports AI governance, responsible AI, data strategy, security, privacy, and compliance. The role also promotes AI literacy and adoption across business units while ensuring scalable, reliable data and AI infrastructure.

Lead strategic customer engagements by discovering operational challenges, architecting and prototyping secure AI and LLM solutions, and delivering high-stakes Proof-of-Value projects. Present solutions and business value to executives, model ROI and TCO, guide implementation and adoption, and ensure measurable value realization. The role requires strong presales, software and data engineering, enterprise integration, domain expertise, and native-level German proficiency.

Lead strategic customer engagements focused on AI transformation and value realization. Diagnose operational challenges, architect and prototype secure LLM and agent systems using advanced RAG and enterprise integrations, and deliver Proof-of-Value projects. Present AI solutions and business impact to executives, guide implementation and adoption, develop reusable methodologies, and mentor junior colleagues. Native or near-native German is required for customer workshops, executive presentations, and stakeholder management.

Build and deploy reliable, measurable, and safe AI agents for real business workflows. Work within Marketing Engineering and growth pods to identify problems, develop end-to-end solutions, evaluate LLM performance, and measure business impact. The role involves productionizing agent systems beyond demos, using Python, SQL, LLM APIs, and orchestration tools, with potential integration into go-to-market data and marketing systems.

Conduct research, market sizing, forecasting, competitive analysis, and thought leadership on enterprise AI services. Develop actionable insights for technology providers and senior executives through published research, presentations, conferences, and client engagements. Assess market trends, demand drivers, customer behavior, and growth opportunities while advising clients, supporting sales, reviewing content, mentoring analysts, and improving research processes.

Leads end-to-end architecture for enterprise data, analytics, and AI solutions in a Microsoft-first environment. Translates business requirements into secure, scalable designs and guides prototyping, implementation, architecture reviews, troubleshooting, governance, and production readiness. Requires deep hands-on experience with Azure data platforms, Power BI, enterprise security, Azure OpenAI, and retrieval-augmented generation patterns.

Manage influencer campaigns end to end across multiple brands and markets. Responsibilities include creator casting, briefing, negotiation, contracting, campaign timelines, budgets, approvals, client communications, performance tracking, reporting, and optimization. The role requires using CPV and campaign KPIs to manage commercial outcomes, ensuring content meets brand and compliance requirements, and operating as a power user of Kyra’s platform and AI tools.