Top Artificial Intelligence Jobs in Munich

The Sales Development Representative Manager will lead an SDR team, focusing on hiring, training, achieving sales goals, and collaborating with regional sales leaders.

As a Customer AI Strategist, you will guide enterprise marketers in Europe through AI Marketing strategies, ensuring measurable results and driving business transformations while managing key client relationships and collaborating with internal teams.

As a Customer AI Analyst, you will optimize customer accounts for AI performance, design prompts for LLMs, deliver insights, and collaborate with teams to enhance service delivery and customer engagement.

The role involves providing legal guidance on global privacy and AI issues, collaborating with teams to ensure compliance, and developing scalable processes.

The AI Applied Scientist Intern will tackle complex problems using deep learning, statistical analysis, and large datasets, collaborating with a team to implement AI solutions that generate economic impact.

Lead horizon scanning and external intelligence to identify AI and disruptive tech opportunities for R&D. Translate trends into actionable briefs, design and run pilots with stage-gates, and scale successful capabilities into production. Influence senior leadership with strategic foresight, build external partnerships, and embed a future-back innovation culture across cross-functional teams to measurably improve R&D outcomes.

Lead on-site AI transformation for mid-market CEOs: own executive relationships, drive fixed-scope first wins on real data, translate problems into build-ready specs, manage rollout to finance-verified outcomes, and codify methods to scale deployments.

Own and prioritise the central AI platform roadmap (agent runtime, evaluation, pipelines, observability). Run experiments, ship v1s or enable product teams, and collaborate with Engineering, Data Science, and leadership to improve AI product speed, quality, and production robustness.

Provide hands-on stabilization of multiple early-stage, often AI-generated codebases: assess, fix bugs, refactor, add missing core functionality (auth, payments), improve performance, implement lightweight testing, and collaborate across teams on fractional hourly engagements.

Own SEO strategy and KPI progress for client accounts, build AI-supported workflows and automations, create repeatable SEO processes, lead client communications and reviews, and drive measurable visibility and business outcomes by combining AI tools and specialist expertise.

Lead design and build a greenfield, AWS-based agentic software delivery platform. Integrate LLMs and agentic coding tools, implement tool orchestration and function calling, deliver end-to-end full‑stack features, evaluate trade-offs between off‑the‑shelf and custom solutions, and drive autonomous engineering capabilities.

Lead full‑stack development of high‑traffic public websites, integrate AI tooling into the SDLC, design scalable backend and performant UIs, maintain cloud infrastructure, CI/CD, monitoring, and testing, and own services under a you‑build‑it‑you‑run‑it philosophy.

Lead end-to-end technical projects for a Voice AI CX platform: scope, plan, manage releases, align product to customer requirements, track metrics, ensure quality, and communicate status to clients and engineering.

Lead QA automation for AI/LLM systems: define validation criteria for non-deterministic models, build automated and performance tests, validate RAG systems, perform API and integration testing, ensure release readiness and trace defects to data/models/requirements.

Lead a cross-functional squad to architect and ship AI-native workflows, integrations, and experimentation infrastructure that scale growth. Build data frameworks, attribution and analytics stacks, run rigorous A/B programs, package repeatable AI enablement toolkits, and collaborate with Engineering to deploy agentic product surfaces.

Lead a global consulting practice to design and deliver supply chain analytics and sustainability strategies for multinational clients; provide strategic leadership, operational excellence, client engagement, and drive business growth.

Lead hands-on applied AI work: prototype demos, accelerate customer POC-to-production, perform technical onboarding, optimize distributed training and inference on GPU infrastructure, research and implement emerging ML techniques, and feed actionable product feedback while producing reusable assets and benchmarks.

Participate in a 3–6 month early career AI R&D program assisting in experiment design and execution for LLMs, reinforcement learning and agentic systems. Write and maintain code for data processing and model evaluation, analyze results, explore efficient distillation, speculative decoding and inference optimization, and collaborate with researchers with potential conversion to full-time.

Lead applied research and system design for agent-native search: develop multi-stage retrieval, ranking, and grounding methods for LLMs working with real-time web data; define evaluation paradigms; optimize relevance, latency, and cost; deploy solutions to production and mentor the engineering team.

Advise AI-focused customers to design scalable AI solutions and manage large-scale GPU deployments. Deliver technical presentations, documentation, and webinars. Collaborate with engineering and product teams to prioritize and convey customer feedback.

Develop and maintain open-source, silicon-optimized AI/ML inference application packages (Inference Snaps) for Linux/Ubuntu Core. Debug, write high-quality code, review upstream contributions, secure and optimize local inference deployments across embedded devices to gateways, and collaborate with a distributed team and stakeholders.

Customer-facing ML/GenAI engineer who advises customers, runs demos and strategic reviews, drives product adoption, partners with sales and engineering, and helps expand accounts by implementing best practices for production ML/LLM systems.

Partner with EMEA AI/ML teams to drive adoption of Arize's observability platform, manage accounts through onboarding and renewals, run workshops/QBRs, identify upsell opportunities, and coordinate technical resources to ensure customers achieve measurable AI outcomes.

Senior technical lead embedding with customer teams to design, architect, and deliver production-grade AI/ML solutions. Drive model optimization, high-performance training (TPUs), efficient serving (vLLM), MLOps, agentic systems, GDPR-compliant private AI, ROI and cost optimization, pre-sales technical support, mentoring, and external thought leadership.

Build and maintain the marketing automation backbone and AI agent integrations. Implement event tracking, data pipelines, CRM customizations, and cross-channel workflows. Prototype agent infrastructure, connect APIs/webhooks, automate go-to-market tasks, and produce analytics and attribution to support growth and experimentation.