Top Artificial Intelligence Jobs in Cologne

Drive product marketing for Renesas automotive microcontrollers: gather global customer requirements, coordinate projects with OEMs/Tier1s, define roadmaps, support sales and support teams, manage product introductions and marketing materials, report KPIs, and coordinate with Japan.

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.

The role involves providing employee relations guidance, handling grievances and investigations, maintaining HR data integrity, and leveraging AI tools to improve processes.

Lead design and deployment of AI agents and workflow automations across Supply & Operations, coach and lead Operational Excellence (Lean/Six Sigma) projects, build OE capabilities, embed continuous improvement and AI-driven workflows into enterprise systems, and lead global OE programs and strategies in External Supply.

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.

Lead the planning, execution, and delivery of robotics projects, coordinating cross-functional teams and managing budgets, timelines, and risks.

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.

Drive independent, high-impact research on frontier AI topics, publish findings, collaborate widely, and mentor new researchers in the field.

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 Major Account Manager will consultatively sell solutions to Fortune 500 accounts, develop relationships, and create strategic account plans to drive business.

Enable and operationalize SAP AI capabilities and developer frameworks across SAP landscapes. Provision and configure Embedded AI services, drive SAP Joule and BTP Joule Studio adoption, establish SAP BTP CAP development environments and transport processes, create enablement documentation and training, and implement custom AI skills to demonstrate business value.

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

The role involves driving new AI software sales, engaging with executives, and leveraging industry expertise to close large enterprise deals.

Design, build, deploy and maintain agentic AI systems and automated workflows for Sales, AM and CSM. Implement autonomous data orchestration, signal-based data architecture, and forecasting pipelines. Integrate agents with CRM (Salesforce/HubSpot) and BI, monitor performance, implement guardrails, and collaborate with PlatformOps, Engineering, Data and Process teams.

Lead full-cycle enterprise sales for an Energy AI platform: engage C-level and technical stakeholders, build data-driven pipeline, refine GTM and sales playbook, run demos, negotiate and close high-value deals, provide customer feedback to Product/Engineering, and use modern tech/automations to scale revenue.

Lead and grow a distributed AI engineering team to build and operate scalable production AI platforms, model-serving, inference and training environments, CI/CD, observability, and integrations. Drive architecture, delivery, vendor evaluation, and operational readiness while partnering with global stakeholders to adopt AI across media and localization workflows.

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.

The role involves selling IFS Loops, an AI-driven solution, targeting industrial markets, with a focus on consultative sales and driving revenue growth.

Design and build production AI systems and distributed backend services that enable genomic reasoning, retrieval, and data platforms. Integrate genomic annotations and interpretation logic, architect high-performance data models and storage across PostgreSQL, DuckDB, Qdrant, Redis, and Spark. Ensure AI outputs are accurate, explainable, and grounded in genomic evidence while collaborating across engineering and bioinformatics teams.

Build and test AI-agent features and internal agent frameworks for a proactive cybersecurity platform. Implement and integrate generative AI systems (agents and RAG), stay current with AI research, and apply innovations to product development and evaluation within a security-focused environment.

Design and build agentic multi-agent AI systems to autonomously plan and execute engineering workflows. Integrate AI coding agents into the SDLC, automate test generation and execution, implement automated incident triage, create secure tool- and API-integration layers, manage agent state/memory, and enforce execution safety guardrails while rapidly prototyping automation solutions.

Own and scale AI enablement: build core orchestration, LLMOps/MLOps platforms and governance, integrate generative AI into product, optimize cost/latency, run PoC-to-production delivery, upskill teams, standardize tooling and vendor strategy, and track adoption/ROI metrics.

Build and productionize AI-native systems for a finance super app: integrate LLMs, agents, RAG, and internal data to automate workflows across support, CRM, onboarding, claims, payments and operations while ensuring evaluation, monitoring, safety and reliability.

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.

Design, build, evaluate, and deploy LLM-driven features and AI systems. Collaborate with engineering and product teams to implement RAG, monitoring, CI/CD, and scalable cloud ML deployments while continuously improving model performance.