Applied AI Engineer

This is a fully remote position, open to applicants in Germany.

📋 Description

• Develop and manage AI functionalities across an enterprise platform.

• Create agent runtimes, manage model routing, implement RAG, facilitate tool/function calling, establish guardrails, and oversee evaluation, monitoring, cost management, latency optimization, and production quality controls.

• Deliver AI capabilities that are reliable in production settings instead of mere demonstrations.

• Transition AI systems from prototypes to monitored production environments.

• Rigorously assess AI behavior using quantifiable frameworks and evidence.

• Collaborate with product and engineering teams to identify when AI represents the suitable solution.

• Convert experimental findings into production-ready features.

• Integrate evaluation processes into the delivery workflow.

• Assist client teams in making educated decisions regarding the genuine value AI can provide.

⛳️ Requirements

• Proven experience delivering software supported by LLMs, ML models, RAG systems, or agentic workflows to actual production users.

• Background in designing or implementing agent runtime, orchestration, model routing, tool/function calling, or AI workflow patterns.

• In-depth knowledge of RAG, grounding, retrieval quality, prompt design, context management, and evaluation methodologies.

• Experience in developing evaluation harnesses, golden sets, regression checks, quality gates, or measurable AI performance frameworks.

• Capability to consider cost, latency, reliability, and safety as essential engineering constraints.

• Experience in establishing guardrails and controls for AI systems, addressing untrusted retrieved content, tool output risks, and potential failure modes.

• Proficiency in monitoring production AI behavior and enhancing systems based on empirical evidence.

• Strong software engineering skills with the ability to collaborate with backend, platform, product, and security teams.

• Excellent communication and collaboration skills suitable for client-facing consulting environments.

• Pragmatic approach with the capacity to prioritize business value and rapidly deliver effective AI solutions responsibly.

• Familiarity with Claude, GPT, Azure OpenAI, open-source models, model routing, fine-tuning, distillation, or small/edge models.

• Experience with MCP, A2A, multi-agent orchestration, AI tool calling, or agent evaluation.

• Experience utilizing LLM-as-judge methods calibrated against human evaluation.

• Knowledge of semantic knowledge management, ontologies, knowledge graphs, or semantic layers.

• Familiarity with AI development lifecycle practices covering data, build, evaluation, deployment, monitoring, and continuous improvement.

• Experience employing AI-assisted development tools while upholding strong review, testing, and safety protocols.

🏝️ Benefits

• Flexible remote work arrangement.

• Permanent direct-hire employee position.

• Opportunity to collaborate with a global multi-billion dollar software conglomerate client.