Applied AI Engineer

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

📋 Description

• Develop and manage AI capabilities within an enterprise platform.

• Create agent runtimes, facilitate model routing, implement RAG, enable tool/function calling, establish guardrails, conduct evaluations, monitor performance, manage costs, optimize latency, and maintain production quality controls.

• Deliver AI functionalities that are dependable in production environments rather than mere demonstrations.

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

• Rigorously assess AI behavior using quantifiable performance frameworks.

• Collaborate with product and engineering teams to identify when AI serves as a suitable solution.

• Convert experimental findings into production-ready features.

• Integrate evaluation rigor into the delivery workflow.

• Assist client teams in making informed choices regarding where AI can generate significant value.

• Provide AI capabilities that are effective, trustworthy, quantifiable, safe, and mindful of costs.

⛳️ Requirements

• Proven experience in deploying software supported by LLMs, ML models, RAG systems, or agentic workflows for actual production users.

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

• Deep 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 quantifiable AI performance frameworks.

• Ability to prioritize cost, latency, reliability, and safety as essential engineering constraints.

• Experience in developing guardrails and controls for AI systems, encompassing untrusted retrieved content, tool output risks, and failure modes.

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

• Strong software engineering expertise.

• Capability to collaborate with backend, platform, product, and security teams.

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

• Pragmatic approach with the ability to prioritize business value and swiftly deliver useful AI capabilities 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 with LLM-as-judge methodologies calibrated against human evaluations.

• Experience with semantic knowledge management, ontologies, knowledge graphs, or semantic layers.

• Knowledge of AI development lifecycle practices spanning data, build, evaluation, deployment, monitoring, and continuous improvement.

• Experience utilizing AI-assisted development tools while upholding rigorous review, testing, and safety standards.

🏝️ Benefits

• Flexible remote work arrangement.

• Permanent direct-hire employee status.

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

• Experience in a client-facing consulting environment.