Top Artificial Intelligence Jobs in Munich

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

Develop and own frontend features for AI-driven, agentic product experiences; collaborate with engineering, product, data science, and AI teams; write clean, testable, secure code; lead technical discussions; and contribute to architecture and scalable foundations across CLI, server, and chat products.

Lead strategy and roadmap for an internal AI platform, coordinate cross-functional teams to implement AI use cases, ensure AI compliance and governance, support GTM for AI features, and manage agile delivery while leveraging data and LLM-driven insights to evolve the platform.

Design, build, and maintain production-grade AI/LLM backend services and APIs. Integrate third-party LLM APIs, develop cloud-native architectures on AWS, extend Terraform infra and CI/CD, implement testing/monitoring, and build agentic orchestration workflows while collaborating with cross-functional teams.

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.

Serve as a forward-deployed technical partner translating customer workflows into scalable AI deployments. Drive adoption, own end-to-end deployments and integrations, build prototypes and demos, troubleshoot solutions, design integration architecture, and feed customer insights to product and engineering teams to scale enterprise adoption.

Design, build, and deploy production AI agents and backend services. Integrate with ERPs and external APIs, handle structured and unstructured data, implement memory/retrieval and orchestration pipelines, and maintain cloud infrastructure, observability, CI/CD, and robustness for scalable agent workloads.

Uncountable seeks a Platform Engineer focused on Generative AI to develop AI-powered tools for scientific R&D, requiring fullstack development skills and a passion for advancing user needs.

As a Senior Full Stack Engineer for the AI Platform, you will build solutions enabling rapid GenAI agent development and deployment, impacting healthcare and other sectors. Your role encompasses designing full-stack applications, applying secure SDLC practices, and collaborating on impactful AI systems.

The Senior AI Product Manager will lead cross-functional teams to define, develop, and manage B2B SaaS products, focusing on customer value and market needs, while utilizing Agile methodologies and Generative AI technologies.

Build end-to-end AI systems and agents for procurement workflows. Improve search/matching, build evaluations and data pipelines, implement structured outputs and guardrails, and support backend scalability and reliability in a fast-paced startup environment.

The Consulting Manager will lead AI transformation programs, work with executives on strategy, drive business growth, represent the company in discussions, and mentor teams.

As a Senior Consultant in Data & AI Strategy, you will advise clients on data-driven strategies, analyze data, manage projects, and develop AI solutions.

Own partnership sourcing, negotiation, and deal execution to drive adoption of Walrus across AI and Web3 ecosystems. Build relationships with AI builders, data vendors, compute networks, and web3 partners; lead contract negotiations; and manage cross-functional integration from signing through execution.

Lead quality engineering for AI-enabled applications: design and run evaluations for LLMs and agents, build automated test harnesses and release pipelines, validate APIs and device integrations, investigate defects, and communicate quality risks to stakeholders. Use AI-assisted tools responsibly to accelerate test design and analysis.

Design, build, and maintain an internal AI provisioning platform for LLM access. Implement observability, logging, alerting, and governance (security, data privacy, rate limiting, cost management). Support cloud-native architectures, CI/CD, and containerized deployments. Collaborate with AI engineers to monitor performance and reliability of production AI systems.

Lead AI and machine learning architecture, mentor teams, drive innovation, and evaluate tools for AI systems development across global teams.

Lead architecture and build an automation and AI-native toolchain (fusing traditional automation with agentic workflows), mentor teams, drive cross-department adoption, standardize practices, and evolve IT operations toward infrastructure-as-code and platform-first models.

Architect and build an AI-native automation and orchestration toolchain (fusing traditional tools with foundation models), enable and mentor early adopter teams, standardize practices across departments, drive infrastructure-as-code and CI/CD adoption, contribute to the IT/Sec operating system, and champion cross-departmental adoption of automation and AI platforms.

Lead regional strategic initiatives and PMO activities across Europe, establish governance, simplify processes, drive AI-enabled productivity, coordinate executive forums, and communicate change to deliver measurable business outcomes.

Lead planning and delivery of high-priority regional initiatives across Europe. Enable executive governance, simplify regional processes, embed AI-enabled ways of working, drive communications and stakeholder engagement, and strengthen the Europe Business Impact Team to ensure measurable business outcomes.

Lead the planning, execution, and delivery of robotics projects, coordinating cross-functional teams and managing budgets, timelines, and risks.

Design and ship AI-driven controlling tools, own the group data foundation, automate monthly closing processes, translate complex cost data into CFO/board-level narratives, and ensure integrity of controlling figures.

Lead end-to-end development of production-ready AI and LLM solutions: identify use cases, design architectures, implement and deploy models (RAG, embeddings, fine-tuning), experiment with new models and tools, collaborate with clients and stakeholders, and mentor junior team members.