Top Artificial Intelligence Jobs in Munich

Seeking a Senior Software Engineer to build AI inference systems. Responsibilities include optimizing GPU kernels, architecting inference stacks, and defining benchmarking methodologies. Requires strong programming skills and experience in ML systems.

Define and execute the product roadmap for AI-driven blockchain security monitoring tools. Collaborate with cross-functional teams, analyze market and customer feedback, deliver features on time, and communicate with stakeholders to align expectations and improve product offerings.

Own the end-to-end process converting product, marketing, and account signals into qualified sales opportunities. Build qualification criteria, routing rules, data enrichment and automation, partner across product/marketing/sales/analytics, create feedback loops, and measure and optimize funnel conversion and data quality.

Lead design and delivery of AI-powered features for CLion and C++ workflows. Architect AI integrations and agent tools, prototype and validate debugging, code-understanding, refactoring, and navigation workflows, build benchmarks and evaluation frameworks, and collaborate with product, ML, QA, and engineering teams to set technical direction and roadmap for AI-assisted C++ development.

Own acquisition, onboarding, and activation for JetBrains AI. Improve product entry points, trials, demos, and onboarding flows. Lead experiments, analyze funnels and cohorts, remove friction, and partner with design, engineering, analytics, marketing, and monetization to drive activation and conversion.

Design and implement agentic tools, translating product needs to production, scale prototypes, improve semantic search, build evaluation pipelines.

As a Consulting Intern, you will work with the AI & Data team to perform advanced analytics, develop predictive models, and assist in client communications for strategic consulting projects.

Own and grow the Data Layer: build and operate ingestion, transformation, reconciliation, and serving pipelines (raw→refined→curated). Use agentic AI tools to accelerate delivery, ensure data correctness, and partner with backend, AI, and product teams to define reliable data contracts.

Design and implement execution primitives for AI/agent workflows in Kestra's Java core, build and maintain plugins to connect LLM providers and agent frameworks, convert agent use cases into reusable blueprints with product, and ensure AI executions are observable, debuggable, correct, and reliable.

Own AI workflows product: discover and validate AI use cases with customers, define roadmap and specs, create reusable blueprints with engineering, and prioritize what not to build.

As an AI-native growth hacker, you will implement a growth strategy, focusing on a specific growth wedge, leveraging AI tools, and measuring performance to scale successfully.

Design, build, and run production agentic workflows and reusable components for delivery processes. Implement RAG-backed knowledge bases, monitoring, evals, observability, and human-in-the-loop feedback to improve agents and integrate them with delivery teams and business tools.

Senior Director analyst providing thought leadership and actionable research on infrastructure and operations AI strategy. Produce insights, presentations, and client advisories; guide AI infrastructure, cloud adoption, integration, governance, and vendor selection. Lead research agenda, mentor analysts, collaborate cross-functionally (infrastructure, engineering, enterprise architecture, cybersecurity), support sales, and represent Gartner at events. Drive process improvements and influence senior stakeholders to align infrastructure and operations with business outcomes.

Design polished, user-centric mobile and web interfaces for BJAK's AI-driven financial products. Translate requirements into wireframes, flows, prototypes and high-fidelity UI. Maintain design system, ensure accessibility and responsiveness, iterate using user feedback, and collaborate with PMs and engineers to deliver pixel-perfect implementations.

Develop and ship features for client projects and in-house products (including mobile AI apps) using TypeScript, React, and Node.js. Work agent-first with AI coding tools, review and harden generated code, debug unfamiliar code, turn loose requirements into working software, and own small end-to-end pieces with senior mentorship.

Work directly with the CTO to build and ship fullstack features to production daily. Contribute to a fully agentic system automating the headhunting process end-to-end, live-working from hackerhouses in Latin America alongside a small founding team.

Design and build backend systems powered by LLMs, develop AI agent workflows and tool integrations, implement RAG pipelines with vector search, handle prompt orchestration and context management, optimize performance and cost, and ship AI features to production.

As a Staff/Senior AI Engineer, you will develop production-ready coding agents and improve AI model capabilities for JetBrains' software development tools. Collaborating with teams, you'll focus on model training, evaluation, and product integration to enhance user experience.

The Applied AI Architect will advise enterprise clients on integrating AI solutions, develop scalable architectures, and support their adoption journey of Claude AI systems.

Lead the core biometric recognition technology team, managing the full lifecycle of ML systems focused on iris and face recognition while ensuring privacy and reliability at scale.

Lead development and scaling of AI-powered clinical applications using LLMs. Gather user and industry requirements, write product specifications, prioritize roadmaps, coordinate sprints and releases, validate quality with engineering and QA, and design generative AI capabilities to streamline pharmaceutical workflows and regulatory documentation.

Lead company-wide AI initiatives: identify high-impact automation use cases, design and implement AI-powered workflows using Make, Claude and Pinecone, collaborate cross-functionally, measure impact, and enable teams to adopt and optimize AI-driven processes.

Develop, maintain, and lead software platforms, tools, and infrastructure for regulated computational pathology products. Implement production-quality features, follow V-model regulated development practices, support risk assessments, establish engineering controls and documentation, collaborate cross-functionally, provide technical leadership, and mentor engineers to ensure compliant, traceable, and scalable AI-enabled medical software delivery.

Design, implement, and maintain software platforms, tools, and infrastructure for regulated AI-enabled computational pathology products. Ensure compliance with regulated development practices (V-model), support risk assessments, verification/validation, traceability, and lifecycle documentation. Provide technical leadership, process improvements, and mentorship across multidisciplinary teams to enable scalable, compliant AI software delivery.

Own end-to-end development of AI-powered product features: design prompts, tools, memory and agent workflows; deploy and stabilize LLMs in production; optimize latency, cost, and reliability; build evaluation frameworks; debug model, orchestration, infra, and UX issues; and collaborate with product and engineering to deliver measurable improvements.