Top Artificial Intelligence Jobs in Berlin

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.

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 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.

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).

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.

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.

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.

Own the UK market as Growth Product Manager: work with installers through calls, site visits and support; improve activation, adoption and retention; ship UK-compliant, reusable product features; set UX/UI standards; collaborate with Product, Engineering, Design, Marketing, Sales and Customer Success.

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 and coordinate technical AI/ML programs bridging research and lab implementation. Plan and deliver projects, manage compute/resources/dependencies, liaise with industry and academic partners, drive proposals and pilots, refine scalable processes, track metrics, and support IP, compliance, and publication efforts.

Lead technical discovery and deliver tailored live demos of LLM-powered solutions to enterprise prospects. Translate customer pain points into AI architectures, build credibility, and feed insights to Product, Marketing, and R&D while partnering with Sales to shape customers' AI vision.

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.

Build end-to-end AI-native product features across frontend, backend, and AI integrations. Design and deploy reliable agent workflows, integrate LLMs/memory/tools, optimize streaming low-latency interactions, improve observability, fallback and recovery mechanisms, and iterate on production failures to increase reliability of multi-step workflows.

Nebius seeks a Senior ML Engineer for AI R&D focusing on applied research in reinforcement learning and agent training, requiring deep expertise in machine learning and software engineering.

Partner with Account Executives to present Arize's GenAI observability platform, lead technical demos and discovery, design and run PoCs, advise on GenAI/LLM best practices, handle technical objections, and build relationships with technical and business stakeholders across prospective customers.

Own and translate SAP consulting knowledge into AI agent workflows; design scalable architectures for SAP landscapes (S/4HANA, ECC); collaborate with enterprise clients during onboarding and rollouts; partner with AI and engineering teams to ensure technical accuracy; build reusable reference architectures and act as domain expert embedding SAP knowledge into the product.

Build and maintain end-to-end AI product features using LLM APIs, including chat UX and backend integrations. Design RAG and retrieval pipelines, agent orchestration, evaluation infrastructure, and scalable FastAPI/Python backends while ensuring security, privacy, and operational monitoring. Collaborate with Product, Legal Engineering, and Design to prototype and ship AI-powered legal workflows.

Develop computer vision models for object recognition and video understanding while evaluating and improving their performance for real-world applications.

Design and iterate UX/UI for an AI-powered OS used by renewable installers. Own end-to-end product design, prototype quickly, improve flows, collaborate with product and engineering, and use data and research to drive adoption.

Lead rapid end-to-end prototyping of LLM-powered agent systems: build working prototypes, design experiments measuring quality/latency/cost/user impact, validate with users, produce reference implementations, and hand off to product teams to inform roadmap decisions.