Applied AI Engineer

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

📋 Description

• Develop and manage AI functionalities across an enterprise platform.

• Collaborate with agent runtimes, model routing, RAG, tool/function invocation, guardrails, evaluation, monitoring, cost management, latency optimization, and production quality controls.

• Release AI features that consistently perform in a production environment rather than just in demonstrations.

• Transition AI systems from prototype stages to monitored production environments.

• Rigorously assess AI behavior and integrate evaluation discipline into the delivery processes.

• Work alongside product and engineering teams to assess when AI is beneficial and when it is not.

• Convert experiments into production-ready features.

• Assist client teams in making well-informed decisions regarding the genuine value AI can provide.

• Deliver AI functionalities that are practical, dependable, measurable, safe, and cost-conscious.

⛳️ Requirements

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

• Background in designing or implementing agent runtimes, orchestration, model routing, tool/function invocation, or AI workflow models.

• Solid understanding of RAG, grounding, retrieval quality, prompt design, context management, and evaluation methodologies.

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

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

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

• Track record of monitoring AI behavior in production and enhancing systems based on evidence rather than opinion.

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

• Excellent communication and collaboration skills suited for client-facing consulting roles.

• Pragmatic approach with the ability to prioritize business value and rapidly deliver effective AI functionalities.

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

• Knowledge of MCP, A2A, multi-agent orchestration, AI tool invocation, or agent evaluation.

• Experience with LLM-as-judge methodologies adjusted against human evaluation.

• Background in semantic knowledge management, ontologies, knowledge graphs, or semantic layers.

• Experience in AI development lifecycle practices covering data, build, evaluation, deployment, monitoring, and continuous enhancement.

• Proficient in using AI-assisted development tools while upholding rigorous review, testing, and safety protocols.

🏝️ Benefits

• Flexible remote work arrangement.

• Permanent employee status.

• Direct-hire employment opportunity.

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