Top Artificial Intelligence Jobs in Cologne

The role involves evaluating AI outputs, correcting texts, analyzing multimedia, and providing culturally relevant content while adhering to guidelines.

Lead end-to-end organic growth programs for B2B tech clients, owning strategy, execution, deliverable quality, renewals, and commercial-impact metrics across a portfolio of up to ten accounts. Prioritize work, set and keep commitments, evaluate recommendations, and partner with a production team that executes briefs, decks, and data.

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.

Design rigorous, deterministic advanced mathematics problems and provide complete verified solutions to train and evaluate state-of-the-art AI models. Produce reproducible, well-documented reasoning and, when needed, computational workflows using Python and scientific libraries. Ensure problems target deep mathematical reasoning and are technically precise.

As an AI Automations Engineer, you will design and build tooling for GTM, Operations, and Finance teams, automating processes and enhancing systems with a focus on AI.

Build production-grade AI agents, LLM apps, RAG systems and automations for fintech workflows (onboarding, KYC, support, risk, CRM). Work with product and engineering to ship, evaluate, and improve reliable, secure, cost-effective AI-enabled systems that replace manual processes.

Lead EMEA go-to-market for Physical AI by sourcing executive-level pipeline, accelerating top accounts, building EMEA-specific playbooks, enabling regional sales, and converting lighthouse wins into sustained cloud consumption across robotics, autonomy, simulation, and related AI-native industries.

Design rigorous, deterministic advanced physics problems and provide complete verified solutions for AI training and evaluation. Create reproducible simulations or computational workflows (using Python and scientific libraries), document reasoning clearly, and ensure technical precision. Contribute to problem design that tests deep multi-step physical reasoning.

Lead and build Axelera's AI Infrastructure Systems division to deliver datacenter-class hardware from accelerator cards and OAM/UBB modules to 1U/2U racks. Own architecture, schematics, PCB/layout review, power/thermal/mechanical design, BMC/firmware, bring-up, validation, qualification, NPI, and ramp with CMs/ODMs. Align roadmaps with silicon, SDK, and product teams, engage customers and partners, set engineering processes, manage budget and vendor relationships, and mitigate technical risks through hands-on leadership.

Lead design, training, and evaluation of LLMs for translation and language-quality tasks; build robust evaluation frameworks; architect agentic multi-model workflows; own model development from data curation to production; run reproducible experiments; collaborate with product and engineering and mentor researchers.

Own the end-to-end process converting product, marketing, and account signals into qualified sales opportunities. Build qualification criteria, routing rules, data enrichment and automation, partner across product/marketing/sales/analytics, create feedback loops, and measure and optimize funnel conversion and data quality.

Lead design and delivery of AI-powered features for CLion and C++ workflows. Architect AI integrations and agent tools, prototype and validate debugging, code-understanding, refactoring, and navigation workflows, build benchmarks and evaluation frameworks, and collaborate with product, ML, QA, and engineering teams to set technical direction and roadmap for AI-assisted C++ development.

Design and implement agentic tools, translating product needs to production, scale prototypes, improve semantic search, build evaluation pipelines.

The AI-First Full-Stack Engineer will lead full-stack development using Node.js and Next.js, integrating AI workflows and orchestrating Claude agent teams for efficient engineering processes, ensuring compliance with healthcare standards.

Own end-to-end product for a slice of Nebius AI compute platform: define strategy, APIs, and roadmaps; drive cross-team delivery; conduct structured discovery; measure adoption and platform outcomes; engage engineering as a technical peer; and close operational feedback loops to improve reliability and customer experience.

Lead development of an autonomous agentic AI scientist for drug discovery: architect multi-step reasoning agents, bridge AI and wet-lab experiment design, prototype to productionize agentic systems, publish research, and collaborate with biological experts.

The Senior Product Manager will own the strategic roadmap, lead market research, manage monetization strategies, and mentor product managers within an AI and EdTech environment.

Author and refine a systems-engineering curriculum for experienced engineers: shape syllabus, define learning objectives, produce and fact-check lessons using AI tools, design hands-on projects and rubrics, and iterate with LX designers to meet milestone deliverables over a 4–6 month, ~15–20 hr/week engagement.

Lead applied research and system design for agent-native search: build multi-stage retrieval, ranking, and grounding methods for LLM-driven, iterative agent workflows; deploy high-throughput, low-latency production systems; define evaluation metrics; run experiments and mentor engineers.

Own end-to-end design, build, deploy, and iterate on production AI systems that improve lead quality, reduce refunds, and automate workflows. Ship customer-facing AI features, agentic workflows, retrieval and context layers, reliable event-driven automations, evaluation datasets and monitoring, and reusable components while connecting technical decisions to business KPIs.

Join a client-facing squad as a hands-on Senior Full-Stack Engineer working across Kotlin backends and React/TypeScript frontends. Apply AI-native delivery practices and agent/harness engineering to accelerate delivery, unblock the team, and share patterns across the organisation while using AWS and cloud data tooling.

Create German-first B2B content (blogs, case studies, landing pages, video concepts) using AI-enabled workflows to educate frontline industrial buyers and drive acquisition; own end-to-end content strategy, production, measurement, and cross-team collaboration.

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 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.

Lead Oyster's data platform and AI strategy, centralize AI initiatives into production systems, build scalable data and MLOps infrastructure, modernize knowledge architecture and semantic search, partner cross-functionally to embed AI into products and workflows, enforce tooling standards and governance, and drive organizational adoption and change management for AI-assisted operations.