Top Artificial Intelligence Jobs in Munich

The role involves leading design for AI-native products at Synthesia, focusing on improving interaction patterns and enhancing user experience in AI-driven workflows.

Lead Data, Analytics, AI, and GenAI presales activities for strategic enterprise opportunities. Facilitate discovery workshops, translate business needs into scalable architectures, lead RFP and RFI responses, and present solutions to executives. Design end-to-end AI and cloud architectures across Azure, GCP, Databricks, and open-source ecosystems. Advise on AI transformation use cases, roadmaps, governance, and implementation, while mentoring delivery teams and developing reusable frameworks, offerings, thought leadership, and customer success materials.

Develop and deploy production-ready generative AI applications using Python, LLMs, RAG, AWS Bedrock, and OpenAI APIs. Responsibilities include model customization, API integration, data preparation, performance tuning, production deployment, documentation, and cross-functional collaboration. The role focuses on applied engineering rather than research and requires experience integrating AI solutions into business applications.

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.

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.

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

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.

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.

Join the Compliance team to own AI and e-commerce legal workflows: GDPR and data protection documentation, AI systems inventory, risk assessments, product/feature reviews, contract and IP issue handling, TOS/privacy updates, and monitoring legal developments. Work with the Ethics & Compliance Officer and review uncensored AI content as needed.

The role involves owning legal and compliance workflows related to AI and e-commerce regulations, focusing on contracts, data protection, and risk assessments.

Build and improve Restream’s web interfaces and user-facing features for the AI Clips team. Design UI and business logic, collaborate with product designers, participate in code reviews, improve system reliability, and evaluate emerging technologies. The role requires strong JavaScript and TypeScript expertise, advanced React knowledge, CSS preprocessor experience, and familiarity with backend development, cloud infrastructure, containers, and continuous deployment.

Design, implement, and deploy AI solutions using LLMs, RAG, and AI agents. Identify AI use cases, evaluate risks and limitations, support digital and data strategy, and collaborate with teams to deliver production-ready solutions.

Lead enterprise AI strategy, operating model, governance, platform enablement, and CoE to deploy safe, compliant, and scalable AI across R&D, Clinical, Manufacturing, Quality, Commercial, and Corporate functions in a regulated pharmaceutical environment.

Conduct hardware-aware ML research and engineering to accelerate AI inference. Build fine-tuning and post-training pipelines, benchmarking and profiling tools, and collaborate with hardware, compiler, and quantization teams to optimize model quality, latency, throughput, and power on novel silicon.

Lead design and ownership of shared libraries, Spring Boot starters, and agentic frameworks. Set standards for agent orchestration, evaluations, and guardrails. Mentor teams on Python-based agents (LangChain/LangGraph), drive adoption, prototype research directions, and improve developer experience across Kotlin backend and client libraries.

Provide EU-focused counsel on AI and privacy regulation (EU AI Act, GDPR, DSA); draft policies, DPA and contractual terms; translate legal requirements into technical and operational controls; advise product, engineering, and go-to-market teams; liaise with regulators and manage compliance programs and risk assessments.

As an AI/ML Engineer, you will develop and optimize machine learning models for mobile apps, collaborating with cross-functional teams to enhance user experiences.

As an AI Product Manager, you will define the product roadmap, collaborate with teams to launch AI features, and drive data-driven decisions.

Lead Data & AI consulting engagements from strategy to delivery: identify high-impact use cases, define roadmaps, guide bespoke AI and platform development, manage stakeholders and project delivery, support sales and proposals, and create reusable assets while representing the discipline externally.

Work as an intern building software and AI application features for production manufacturing systems. Collaborate with senior engineers to troubleshoot, document, and ship solutions, integrate the platform into customer environments, and translate customer requirements into technical implementations while learning production processes, IT infrastructure, and AI product deployment.

Build and operate shared AI platform infrastructure for LLM applications, agents, RAG, tool calling, and AI workflows. Develop data and knowledge pipelines, secure enterprise integrations, reusable frameworks, deployment and observability standards, and developer tooling. Take AI systems from experimentation to reliable production while ensuring security, privacy, governance, scalability, quality, and cost efficiency. Collaborate across Engineering, Product, and IT to establish practical AI platform patterns and guardrails.

Lead enmacc's transition to an AI-first trading platform by developing AI solutions and predictive models tailored for energy trading, overseeing a unified Data & AI team, and driving product innovation.

Provide research and advisory to global CFOs and Controllers on transforming controllership processes (AP, AR, financial close) using AI, automation and finance technologies; produce published research, vendor evaluations, and client-facing presentations; collaborate with analysts and deliver strategic, actionable recommendations to improve financial reporting and automation outcomes.