Top Artificial Intelligence Jobs in Hamburg

The Principal Engineer will lead the design and delivery of core platform capabilities, focusing on scalable systems, AI application, and mentoring engineers while driving architectural decisions and improving operational systems.

Own partnership sourcing, negotiation, and deal execution to drive adoption of Walrus across AI and Web3 ecosystems. Build relationships with AI builders, data vendors, compute networks, and web3 partners; lead contract negotiations; and manage cross-functional integration from signing through execution.

Owns commercial success, revenue, and strategic relationships for embedded HR technology partners. Responsibilities include managing a $10M+ annual bookings target, developing partner sales motions, enabling partner sellers, driving pipeline and ARR growth, resolving commercial issues, leading executive business reviews, expanding partnerships, coordinating cross-functional teams, and managing partner account managers and embedded sales leads.

Lead Rasa’s product organization and define strategy for its enterprise conversational AI platform. Manage and develop a team of product managers, own product roadmaps and lifecycle decisions, and partner with engineering, sales, and marketing on product definition, pricing, packaging, and go-to-market. Use customer research, market analysis, competitive intelligence, and developer feedback to guide innovation and foster a strong ecosystem across cloud, on-premises, and open-source deployments.

Assess and evaluate AI-generated technical content, craft and answer advanced ML/AI questions, identify errors and hallucinations, rank responses by correctness and clarity, and provide precise feedback to improve model performance.

Leads digital transformation across procurement by implementing and optimizing SAP, Coupa, ERP, e-sourcing, and supplier management technologies. Oversees data governance, integration, process improvement, category and spend analytics, supplier performance monitoring, and cross-functional project delivery. Evaluates emerging capabilities such as AI and RPA, manages stakeholder relationships, mentors team members, and drives procurement technology innovation and operational efficiency.

Build Solidgate’s new ML/AI function, developing production machine learning models, recommendation systems, and real-time transaction-routing decision systems. Own experimentation from ideation through A/B testing and deployment, engineer features from high-cardinality transactional data, integrate emerging AI technologies, and collaborate with Product, Engineering, and Data Platform teams on training and analytics pipelines.

Owns planning, activation, optimization, testing, budgeting, and reporting for paid campaigns across TikTok, Meta, and YouTube. Manages $1M+ budgets, presents data-driven recommendations to clients, tracks platform changes, and partners with strategy and creative teams. The role also mentors a Paid Media Executive and establishes team standards for campaign QA, reporting, naming conventions, and optimization practices.

As a Sr. Applied AI Engineer at Zapier, you will build and enhance AI platform capabilities, focusing on LLM Ops and ML Ops to support scalable AI development across teams.

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.

Advise clients on enterprise and function-specific AI and data strategy, assess AI maturity, define platform and operating models, build business cases and roadmaps, embed Responsible AI, lead workstreams and large-scale delivery, and tie AI initiatives to measurable business outcomes while engaging senior stakeholders.

Citrine Informatics invites applicants to submit resumes for general opportunities. They review applications periodically for potential new roles in AI-driven materials and chemicals.

Design, develop, and deploy agent-based AI solutions and LLM integrations; build backend and integration components, connect systems via APIs, automate business processes with workflow/AI platforms, and ensure scalable, secure production operations.

Embed with enterprise clients to design, build, and deploy AI-native agentic systems. Lead product orchestration, agent architecture, multi-provider AI integrations, cloud-native engineering (Kubernetes, Docker, serverless), CI/CD and IaC, domain-specific workflow deployments, measurement and observability, and stakeholder communication including workshops and POCs.

Own and scale Impossible Cloud's global GTM for GPU and AI infrastructure: define segmentation, pricing, and playbooks; build and lead global GTM teams; align product and engineering with market needs; drive partnerships, enterprise deals, and thought leadership to accelerate adoption.

Develop and maintain backend services for AI-driven digital pathology, collaborating with cross-functional teams on technical solutions and automation tools.

The role involves translating business requirements into automation and AI solutions, improving R&D processes, and operating collaboration tools.

Lead research and development of AI accelerator/NPU IPs for embedded products. Architect RTL and hardware to meet power/performance/area targets, collaborate with compiler and software teams, model systems, and mentor cross-functional teams toward chip tape-out.

Lead product direction, roadmaps, priorities, standards, and success metrics for major AI neobank areas. Guide PMs, product owners, designers, and engineers across multiple squads while balancing user experience, data, engineering, regulatory, operational, and business constraints. Drive launch quality, post-launch learning, continuous improvement, and a high-performing product culture across financial services including insurance, payments, savings, investing, and travel.

Lead product direction, roadmaps, standards, metrics, execution, and quality for major areas of KIRA’s AI Neobank App. Guide PMs, product owners, designers, and engineers across multiple squads and financial services, including insurance, payments, savings, investing, and travel. Translate regulatory and business constraints into product decisions, drive launches and iteration, and promote a fast, user-focused product culture.

Leads major product areas for KIRA’s AI Finance App, owning product direction, roadmaps, standards, metrics, execution, launch quality, and continuous improvement across multiple squads. The role involves guiding PMs, product owners, designers, and engineers while balancing UX, data, engineering, regulatory, operational, and business constraints across insurance, payments, savings, investing, and travel products.

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.

Develop and validate AI-based CT image formation solutions, including reconstruction, denoising, image quality improvement, and dose reduction for conventional, spectral, and photon-counting CT. Apply deep learning and data science expertise, collaborate with interdisciplinary R&D teams, provide technical guidance, and help transfer research into clinically meaningful imaging innovations.

Support growth and go-to-market strategy for an AI-native Photostudio SaaS venture. Responsibilities include running paid, organic, and outbound growth experiments; supporting performance marketing across LinkedIn, Meta, and Google; conducting market, competitor, and user research; creating reports and presentations; developing dashboards; and contributing to social media and short-form video content.

Build and deploy production-grade LLM capabilities for the Kayzen Console. Responsibilities include developing AI-backed APIs and full-stack features, implementing RAG, embeddings, agents, and tool calling, and establishing evaluation, monitoring, observability, and feedback systems. The role optimizes quality, latency, reliability, and cost; troubleshoots production issues; collaborates with Product, ML, and Engineering; and turns prototypes into maintainable AI products.