Top Artificial Intelligence Jobs in Cologne

Design and deliver AI-powered experiences for Datadog Notebooks. Build reliable backend services integrating LLMs and AI agents, manage model nondeterminism with evaluation/testing frameworks, partner with product/design, provide technical leadership, and operate production systems (on-call).

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.

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.

Lead strategic customer engagements as the accountable program lead for enterprise Celonis customers. Drive adoption, value realization, executive relationships, change management, and cross-functional delivery while mentoring teams and championing customer advocacy and industry-specific transformation (logistics focus).

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

Lead strategic customer engagements to drive AI-driven process transformation using Celonis. Serve as accountable program lead, engage C-level stakeholders, mobilize cross-functional teams, mentor staff, build Centers of Excellence, and ensure value realization, adoption, and customer advocacy—with strong focus on logistics/transportation clients and German-language engagement.

Lead identification, delivery, and adoption of AI initiatives across EMEA. Engage senior stakeholders, manage vendors, design training and curricula, apply agile and design thinking, and build organizational AI capability while measuring and communicating delivered value.

Design and architect pragmatic AI solutions using cloud and third-party LLMs; translate business needs into AI-powered systems, prototype POCs, design agent/multi-agent integrations, define standards, and coach teams on Google Cloud AI products.

Lead AI governance across the model lifecycle: build scalable governance platforms, define controls for agentic AI, translate laws (e.g., EU AI Act) into actionable processes, partner with engineers and compliance, and improve AI risk management and auditability.

The Senior Solutions Engineer collaborates with customers to design and sell innovative internet solutions, manage technical queries, and support internal teams, focusing on cloud and security technologies.

As a Lead/Staff Full Stack Engineer, you'll design and develop full-stack applications and AI agents for the GenAI platform, focusing on rapid deployment and impactful decision-making for various industries. You'll also mentor engineers and lead major projects.

As a Principal Full Stack Engineer, lead the development of the GenAI platform, design full-stack applications, and mentor engineers. Build scalable systems for AI agents affecting key industries, ensuring security and reliability.

Lead the Sales Models portfolio (NBA, Churn, CLV), set roadmap and technical standards, manage a cross-functional Data Science and Engineering team, integrate models into Dynamics 365 and Power BI, translate model outputs into C-level decisions, and build governance and feedback loops from field sales to model iteration.

As a Senior Full Stack Engineer for the AI Platform, you will build solutions enabling rapid GenAI agent development and deployment, impacting healthcare and other sectors. Your role encompasses designing full-stack applications, applying secure SDLC practices, and collaborating on impactful AI systems.

Lead global marketing and corporate communications to define Multiverse's narrative, positioning, and GTM for AI/quantum products. Partner with the CEO, build and scale the marketing & communications team, own product messaging, PR, executive positioning, agency relationships, and measure impact on awareness and enterprise pipeline.

Lead AI and machine learning architecture, mentor teams, drive innovation, and evaluate tools for AI systems development across global teams.

Lead Embedded AI efforts: benchmark and prototype proofs-of-concept, develop tools/methods, support hardware/AI SoC selection, optimize real-time implementations on DSPs/accelerators, and coordinate with algorithm and system teams for ADAS/AD features.

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.

Define the vision and roadmap for an Agentic AI platform, prioritize platform capabilities (LLMOps, MLOps, observability, governance, secure AI), and partner with engineering, data, security, and business teams to build scalable, reliable, and easy-to-adopt platform services on Azure using IaC and CI/CD.

Lead product vision and roadmap for AI-native R&D tools in materials science. Drive discovery, validation, and delivery of AI features by coordinating data scientists, engineers, chemists, and vendors; perform user research, define requirements, manage backlog, and measure adoption and ROI to scale impactful AI solutions.

Partner with business and data teams to identify high-value AI use cases, design and prototype LLM-based solutions (RAG, agents, prompts), integrate with enterprise data via Azure Databricks, and drive adoption through change management and scalable deployments.

Manage various AI/ML projects from concept to development, coordinating teams, managing risks, and ensuring project goals are met. Responsible for documentation and financial planning.

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.

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.

Drive solution sales for Microsoft Cloud and AI within Automotive and Manufacturing enterprise accounts. Qualify opportunities, build stakeholder relationships, orchestrate deals with partners and consulting teams, align AI/cloud strategies to business outcomes, use analytics to prioritize pipeline, and support secure AI transformation and customer success.