Advertising That Lasts
Applied AI Engineer (f/m/x) - Remote
Location
Germany
Posted
39 days ago
Salary
0
Seniority
Mid Level
No structured requirement data.
Job Description
Applied AI Engineer (f/m/x) - Remote
exmox GmbH
Your Mission This is a company built for growth. At exmox, you'll work on real systems at scale. We build high-performing consumer products used by millions in a highly competitive, global mobile gaming ecosystem powered by event-driven architectures, complex business logic, and fast feedback loops. We're scaling fast around one of the most exciting innovations in mobile gaming: a rewarded user engagement and acquisition platform that helps publishers acquire and retain players. That means distributed systems, evolving architectures, and problems that don't have textbook answers. We are looking for an Applied AI Engineer (f/m/x) to design, build, and ship production-grade systems that weave large language models, agentic workflows, and generative AI tools into the core of our product and business operations. You will own the full lifecycle from prototyping an AI-powered automation to hardening it for production on AWS working in Python and FastAPI on a modern cloud-native stack. This is not a research role. You will spend your time writing backend services, designing robust integrations with third-party AI APIs, and building agentic pipelines that replace manual business processes with intelligent, self-improving workflows. If you're excited by complex systems, high traffic, and applied AI at scale, we want to hear from you. What You’ll Own - Backend development: Design and build performant, well-tested Python/FastAPI services that power AI-driven features and automations. - Agentic workflow design: Architect multi-step AI agent pipelines using frameworks such as LangGraph, CrewAI, or custom orchestration layers. Define tool schemas, manage state, implement retry/fallback logic, and ensure human-in-the-loop controls where required. - LLM integration: Integrate LLM providers (OpenAI, Anthropic, open-source models) via APIs and SDKs. Manage prompt engineering, context-window strategies, structured output parsing, streaming, caching, and cost optimization. - Generative media API integration: Connect and orchestrate external AI creative tools such as Arcads, Seedance, Runway and more into automated content pipelines. - Business process automation: Identify, propose, and implement AI-native automations across the organization from content creation workflows to data enrichment, QA, customer support, and internal tooling. - Cloud & DevOps: Collaborate closely with our Platform team to deploy and operate services on AWS. Manage observability, and cost governance for AI workloads. - Collaboration: Work closely with product, design, and business stakeholders to translate ambiguous business needs into concrete AI-powered solutions. What You Bring - Backend engineering: 5+ years of production Python experience, with strong hands-on knowledge of FastAPI or similar frameworks - LLM integration: Proven experience building LLM-powered applications including prompt engineering, context management, structured outputs, and cost optimization across providers like OpenAI or Anthropic - Agentic systems: Hands-on experience designing multi-step agent pipelines using frameworks such as LangGraph, CrewAI, or custom orchestration layers, including state management, tool schemas, and fallback logic - API integrations: Experience integrating third-party APIs at scale, ideally including generative media or creative AI tools - Engineering mindset: You write clean, tested, production-ready code and take full ownership of what you ship - Stakeholder collaboration: Able to translate ambiguous business problems into concrete technical solutions, working closely with non-technical stakeholders Nice to have: - Generative media: Exposure to video, image, or audio generation APIs such as Runway, Seedance, or similar - Human-in-the-loop: Experience with AI quality assurance or approval workflows - Scale-up experience: Background in fast-paced, product-led environments What You Can Expect - Ambitious people, real ownership. Work with driven people who challenge each other openly and take full ownership of meaningful parts of the business. - A company that prioritizes growth, performance, and impact. Comfort isn’t the goal here, progress is. We set a high bar and focus on delivering real results. - A highly ambitious environment with a clear goal. Building the next European tech challenger is not just an idea, it is our mission. Everything we do is driven by the ambition to compete at the highest level and win. - Direct exposure to leadership and real decision-making. You’ll work closely with experienced leaders, contribute to strategic discussions, and see how decisions shape the business in real time.
Related Guides
Related Job Pages
More AI Engineer Jobs
Senior Applied AI Engineer
AscentHelping customers connect data, software and purpose to drive extraordinary outcomes.
• Build and maintain scalable data pipelines and transformation workflows • Implement data quality checks, validation frameworks, and monitoring systems • Design and operationalize evaluation frameworks for datasets and ML outputs • Package and deliver production-ready datasets with clear documentation and QA standards • Develop ML-assisted tools and workflows to improve data processing and delivery efficiency • Generate, augment, and validate synthetic datasets to support client and internal use cases • Deploy lightweight ML/LLM-powered solutions to solve operational bottlenecks • Work directly with delivery teams to implement and maintain production workflows • Debug, troubleshoot, and resolve technical issues across data pipelines and systems • Continuously improve tooling, processes, and measurement approaches used in delivery • Identify and implement practical improvements that increase speed, reliability, and quality of delivery outcomes
• Design and build performant, well-tested Python/FastAPI services that power AI-driven features and automations. • Architect multi-step AI agent pipelines using frameworks such as LangGraph, CrewAI, or custom orchestration layers. • Integrate LLM providers (OpenAI, Anthropic, open-source models) via APIs and SDKs. • Connect and orchestrate external AI creative tools such as Arcads, Seedance, Runway and more into automated content pipelines. • Identify, propose, and implement AI-native automations across the organization from content creation workflows to data enrichment, QA, customer support, and internal tooling. • Collaborate closely with our Platform team to deploy and operate services on AWS.
AI Engineer
StravitoOne place for all your market research. Centralise your insights and make them accessible to teams everywhere.
• Create AI-powered workflows that eliminate tedious insights work: automatic report generation, intelligent summarization across hundreds of sources, and proactive insight discovery from vast content libraries • Integrate cutting-edge AI capabilities: Implement multi-model orchestration (LLMs, embeddings, classifiers), build robust fallback systems, and ensure consistent performance across diverse document types and languages • Collaborate on full-stack AI delivery: Partner with product and engineering teams to ship features end-to-end, from ML pipelines to APIs to user interfaces that make AI accessible for non-technical users
• Build feedback loops from outcomes → strategy improvements (signals, risk, timing) • Develop evaluation frameworks to identify what drives profitable trades • Automate strategy generation, backtesting, and deployment • Design multi-agent learning and fleet coordination systems • Own ML/LLM systems end-to-end: data → model → production → measurable impact



