Top Artificial Intelligence Jobs in Hamburg

Lead the Agentic Discovery product chapter, initially owning business tooling, dashboards, transparency, and controls for AI-powered commerce experiences. Define strategy, align ML, engineering, design, and go-to-market teams, scale experimentation, launch reliable LLM-powered experiences, and establish metrics tied to usage, conversion, revenue, and engagement. The role will expand to chapter-wide leadership across on-site, offsite, and integrated agentic discovery surfaces.

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.

As a Product Designer at voize, you'll create intuitive mobile experiences for healthcare professionals, translating complex workflows into usable designs while collaborating with product teams through design and implementation phases.

Design, implement, and optimize high-performance attention and foundational AI kernels for GPUs, NPUs, ASICs, and other accelerators. Build reusable attention-framework abstractions, profile workloads, develop benchmarks and correctness tests, analyze hardware and compiler behavior, and improve production inference performance. Collaborate with hardware and software teams, document designs, resolve ambiguous performance issues, and mentor engineers while supporting new accelerator architectures and AI workloads.

Lead Trade Nation’s data and AI strategy, with emphasis on deploying AI into business workflows and enabling measurable adoption. Own the data warehouse’s business-facing gold layer, semantic models, data quality, analytics engineering standards, and self-service analytics. Lead and develop data analysts while partnering with engineering, compliance, and senior stakeholders. The role requires financial services experience, strong SQL and data modelling skills, cloud data platform expertise, and the ability to deliver AI initiatives from concept through production.

Leads consultative discovery, technical qualification, solution design, executive presentations, and sales campaigns for AspenTech industrial software. Partners with sales teams to align technology with measurable customer value, develops industry-specific messaging, engages senior executives, provides product feedback, coaches sales personnel, and represents the company at industry events. Requires extensive industrial software or solution consulting experience, technical domain expertise, multilingual fluency, and European work authorization.

Serve as the founding customer-facing engineer for Kimchi, leading product demonstrations, customer workspace setup, inference API integrations, model routing optimization, and governance policy implementation. Configure agent workflows, integrations, budgets, cost attribution, and access controls. Translate customer feedback into product improvements while identifying opportunities for revenue expansion. The role combines hands-on LLM and inference expertise with customer enablement and commercial thinking in a remote-first environment.

Lead development and execution of AI and automation roadmap for Western Europe Amazon e-commerce. Build AI-driven discovery and recommendation strategies, create automated reports and predictive analytics, drive AI tool adoption, ensure responsible AI governance, and run test-and-learn pilots to scale successful e-commerce AI use cases across Amazon markets.

AI/ML Engineers will build and deploy AI-native products, autonomous agents, LLM applications, RAG systems, and production ML pipelines. Responsibilities may include integrating AI into crypto infrastructure and consumer products, fine-tuning and evaluating models, optimizing inference, and developing agentic workflows and machine-to-machine payment systems. Engineers will work end-to-end with high-ownership teams in fast-moving environments.

Leads technical pre-sales engagements for Microsoft Azure cloud and AI infrastructure across German financial services customers. Designs secure, scalable, resilient, compliant, and sovereign architectures; modernizes Windows, Linux, SAP, Oracle, VMware, and application workloads; and guides migrations, containerization, networking, security, and hybrid-cloud solutions. Conducts workshops, prototypes, proofs of concept, and pilots, partners with sales teams to build pipeline, and drives production Azure deployments.

Serve as a customer-facing AI solution architect and trusted advisor, helping organizations adopt Copilot Chat, AI Agents, and Microsoft 365 Copilot. Translate customer challenges into high-ROI architectures, lead technical and business decision-maker engagements, apply prompt engineering and agent-building expertise, support adoption and change management, and identify expansion opportunities with sales and technical teams.

Serve as a technical-strategic partner for AI Decisioning customers, leading use-case delivery from discovery through go-live and expansion. Collaborate with engineers, executives, marketers, and IT stakeholders to define requirements, explore customer data, recommend marketing improvements, manage project risks, and develop delivery best practices. The role also contributes to AI Decisioning product strategy and requires customer-facing consulting, strong communication, and 10–25% travel.

Drive business development and close high-value enterprise deals with global biotech and biopharma accounts across Europe. Own strategic customer relationships, deliver recurring revenue, partner with technical and customer success teams on complex proposals, provide market insights for product direction, build industry credibility, and improve enterprise sales processes and playbooks.

The AI Engineer will build data pipelines and improve ML systems for reliability in production. Responsibilities include schema design, data infrastructure, and model evaluation, ensuring high-quality outputs and integration with product workflows.

Lead customer deployments of Kubernetes and vCluster on bare-metal GPU infrastructure, configuring GPU nodes, networking, storage, RDMA, and InfiniBand. Validate production-ready managed Kubernetes environments, troubleshoot complex infrastructure, transfer operational knowledge, document reusable deployment playbooks, and provide feedback to Engineering and Product. Support pre-sales proof-of-value engagements and help AI cloud and factory customers independently operate and scale their platforms.

Conduct advanced research in artificial intelligence and machine learning, including deep learning, graphical models, reinforcement learning, computer perception, natural language processing, and data representation. Define complex business problems, design and deliver modeling solutions, evaluate model performance, establish scientific and engineering specifications, and build analytical roadmaps. Assess production implementation requirements, improve data capture methods, apply statistical and mathematical techniques, and resolve root causes and process bottlenecks.

Own the strategy, roadmap, and delivery of customer-facing AI agents and workflows for trades businesses. Identify high-value customer problems, lead discovery through production, define AI evaluation and quality standards, monitor performance, and demonstrate measurable customer and commercial outcomes. Partner closely with Engineering, UX, Sales, RevOps, and Customer Success on technical trade-offs, adoption, monetization, and cross-team dependencies.

Build and ship production-grade full-stack software integrated with agentic AI systems. Responsibilities include integrating LLM APIs, using AI-assisted development tools, evaluating AI-generated outputs, building application and API layers, tracking AI productivity KPIs, and supporting Agile delivery from design through production. Contribute to reusable components, AI tooling standards, and integrations involving agent architectures, RAG pipelines, and enterprise AI workflows.

Own outbound sales and pipeline generation through phone, email, and LinkedIn outreach. Identify target accounts, cold call decision-makers, book qualified demos, refine messaging and objection handling, track conversion performance, and collaborate with GTM, product, and marketing teams. The role offers progression into SDR Team Lead or Account Executive responsibilities.

Manage multi-country payroll operations, compliance, audits, controls, vendor relationships, payroll analysis, and process improvements. Lead payroll system automation and scalability initiatives while ensuring accurate and timely processing across jurisdictions. Partner with finance, HR, treasury, and external providers, monitor regulatory changes, and mentor a global payroll team in a distributed technology environment.

Lead a small engineering team building and shipping AI-powered SaaS features. Set technical direction, establish standards for observability, testing, security, scalable architecture, and AI evaluation, while managing delivery timelines and team development. Remain hands-on by designing and implementing production AI systems using LLMs, embeddings, RAG, vector databases, and related tooling. Partner with Product and leadership on prioritization, architecture, resourcing, and risk management.

Own the DACH market launch for Nebuly, generating pipeline through an established enterprise network and managing the full B2B SaaS sales cycle. Target mid-market and enterprise accounts with €100K+ ACV potential, navigate complex stakeholder groups, build business cases, negotiate, and close deals. Represent Nebuly at market events, collaborate with sales engineering and partners, and develop system integrator and advisory relationships. The role requires German and English fluency, strong enterprise relationships, technical sales ability, and experience closing large contracts without inbound or SDR support.

Lead NVIDIA’s developer relations strategy across EMEA Smart Spaces and Local Government ISV ecosystems. Build partner relationships, deliver technical enablement, support integrations, guide startups, and drive adoption of NVIDIA AI and computing platforms. Collaborate with sales, solution architecture, engineering, product, and marketing teams; translate partner needs into product feedback; demonstrate AI solutions; and influence technical and commercial growth. The role requires deep AI/ML and generative AI expertise, technical collaboration skills, and experience scaling developer programs.

Leads end-to-end architecture for enterprise data, analytics, and AI solutions in a Microsoft-first environment. Translates business requirements into secure, scalable designs; guides prototyping, implementation, reviews, troubleshooting, and production readiness. Requires deep Azure data platform, Power BI, enterprise security and governance, Azure OpenAI, and RAG experience. The architect provides hands-on technical leadership and ensures solutions meet operational, compliance, cost, and supportability standards.

Join Welo Data’s Hungarian contributor network for flexible, remote AI data projects. Depending on project needs, contributors may annotate text, images, or audio; evaluate search results, advertisements, or chatbot responses; create and test prompts for large language models; and assess cultural and linguistic accuracy. Projects vary from several days to weeks, with scope, timelines, and compensation provided before participation.