Top Artificial Intelligence Jobs in Germany

As a Software Engineering Intern at Reonic, you'll develop product features and AI-powered workflows for renewable energy, working closely with experienced professionals. You'll own projects and see your code go live, contributing to the deployment of renewable energy solutions.

Own organic growth and AEO/AIO performance: set roadmap from keyword/prompt research to programmatic systems, reposition Softr across LLMs, lead technical and programmatic SEO, build link/citation and Reddit authority, and partner with Content, Product, and Engineering to report performance and translate algorithm and LLM changes into action.

Own end-to-end feature delivery for an AI-native fullstack product: translate user journeys into specs, implement full-stack features, build Playwright E2E suites, set SLOs and observability (Sentry, OpenTelemetry), manage incidents, design GDPR-aligned EU-only hosting architectures, lead AI-agent workflows and technical decisions, and document architecture (ADRs).

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.

Coordinate day-to-day production between key accounts and production teams. Break projects into tasks, track progress, flag delays, ensure complete briefs, manage client feedback and approvals, and oversee multiple clients and formats in parallel. Operational role focused on execution with fast turnarounds; on-site presence in Hamburg required three days weekly.

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.

Build and ship production LLM-powered product features, integrate and debug AI workflows, design validation and fallback logic, implement evaluation and quality checks, and support self-hosted and commercial model deployments while improving reliability, latency, and user value.

Lead regulatory resilience for AI and operational resilience by implementing EU AI Act and DORA controls. Manage AI model classification, conformity assessments, third-party ICT risk, TLPT and BCP exercises, algorithmic audits, and act as primary regulator liaison to ensure compliance and operational anti-fragility.

Build and ship LLM-powered product features end-to-end: design workflows, integrate models into production, implement validation and evaluation loops, improve quality/latency/reliability, debug AI failures, and use AI development tools daily.

Build and ship LLM-powered product features from idea to production. Design LLM workflows, structured outputs, validation and fallback logic. Improve quality, reliability, latency, and cost; integrate AI capabilities into backend systems; build evaluation loops and tests; debug failures across inputs, data, models, and user flows.

Build and ship production-ready AI product features: design LLM workflows, validation and fallback logic, integrate models into backend systems, improve reliability/latency/cost, build evaluation and quality checks, and debug AI feature failures across inputs, outputs, data and user flows.

Build and ship production LLM-based product features, improve AI workflows for quality, latency, and reliability, design validation and fallback logic, integrate models into backend systems, and maintain evaluation/testing loops while using AI development tools daily.

Support project management and business development by driving project delivery, communicating with clients, assisting strategic planning, and working with data science/ML teams. Contribute to client acquisition and help scale the startup under mentorship while gaining hands-on experience in AI-focused solutions.

Lead market-shaping go-to-market and enterprise sales for Vicoland's AI-first SaaS platform. Own client portfolio from C-level advisory to delivery oversight, supervise Vico teams, integrate AI into solutions, and drive long-term account growth while contributing to company strategy and scaling.

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.

Design and build AI-first, production-grade agentic solutions: integrate LLMs, RAG, embeddings, and agent workflows; own the full dev pipeline; lead architecture, code reviews, and mentor engineers; collaborate with product and UX to deliver scalable, maintainable AI features.

The PhD researcher will focus on AI-driven semantic structure extraction, automated reasoning modeling, and personalized content generation, supporting interdisciplinary research and teaching activities in AI and NLP.

Design, prototype, and deploy end-to-end AI-driven automations using existing LLMs, RAG, vector DBs and orchestration tools (e.g., n8n). Partner with cross-functional teams to prioritize high-ROI opportunities, build modular workflows, establish governance/guardrails, and monitor ROI and reliability. Collaborate with CEO & CTO to align solutions with core infrastructure and enable non-technical teams to use automations.

The Director of Data & AI will develop a product strategy for Upvest's data, oversee AI product development, and lead a high-performing team in a regulated fintech environment.

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.

Research and engineer large multimodal and reinforcement-learning models for robotic agents: design, train, evaluate models; prototype in simulation and on hardware; build data pipelines, simulation environments, and distributed training infrastructure; collaborate to scale promising approaches into production and publish results.

Design and build research prototypes and production-capable systems to enable portable, interoperable agent and model workflows. Develop model routing, provider abstractions, memory and context representations, benchmarking suites, and evaluation protocols. Run ML experiments, implement robust APIs and integration layers, collaborate across research and engineering, and communicate results via reports, demos, publications, and open-source releases.

Lead the product for the Italian market: engage installers through calls, visits and support; drive activation, adoption and retention; build local-compliant features and convert them into reusable platform capabilities; collaborate with engineering, design, marketing, sales and CS; review UX/UI and ship improvements.