Applied AI Engineer

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

📋 Description

• Develop and manage AI functionalities within an enterprise platform.

• Create agent runtimes, model routing, RAG, tool/function invocation, guardrails, evaluation, monitoring, cost control, latency enhancement, and production quality assurance.

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

• Conduct thorough evaluations of AI behavior.

• Collaborate with product and engineering teams to ascertain when AI solutions are suitable.

• Provide AI capabilities that are useful, reliable, measurable, safe, and cost-effective.

• Transform experiments into production-ready features.

• Integrate evaluation practices into the delivery workflow.

• Assist client teams in making well-informed decisions regarding the real value of AI.

⛳️ Requirements

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

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

• Deep understanding of RAG, grounding, retrieval quality, prompt design, context management, and evaluation strategies.

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

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

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

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

• Strong software engineering abilities.

• Proficient in collaborating with backend, platform, product, and security teams.

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

• Pragmatic approach with the capacity to prioritize business value and deliver practical AI capabilities swiftly and 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 invocation, or agent evaluation.

• Knowledge of LLM-as-judge methodologies calibrated against human evaluation.

• Experience with 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 utilizing AI-assisted development tools while maintaining rigorous review, testing, and safety protocols.

🏝️ Benefits

• Flexible remote work arrangement.

• Permanent employee status.

• Direct-hire employment opportunity.

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

• Work in a client-focused consulting environment.