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.
