Senior Applied AI Engineer

This is a fully remote position, open to applicants in United Kingdom, +6 more countries.

📋 Description

• Develop and deliver AI-driven product features for Pleo’s clients, taking ownership of results from start to finish for a designated area.

• Create and implement comprehensive RAG systems, encompassing chunking strategies, selection of embedding models, optimization of retrieval processes, and quality assessment.

• Manage the entire AI-product lifecycle, which includes designing prompts, overseeing context and state management, establishing agentic loops, parsing outputs, addressing edge cases, and ensuring safe deployment in production.

• Construct evaluation datasets and automated evaluation workflows.

• Enable production observability for AI features through effective logging, drift detection, quality monitoring, and alerting mechanisms.

• Work in collaboration with Product and Design teams to define AI features from foundational concepts.

• Collaborate with the GenAI Platform team to assess infrastructure requirements and encourage the adoption of platform tools.

• Provide support to engineers via reviews, collaborative work, and technical guidance.

• Acquaint yourself with Pleo’s codebase, tools, and strategic roadmap.

• Contribute to defining the strategy for AI feature development and influence the GenAI Core roadmap.

• Partner with Product and Data teams to deliver the initial feature into production.

⛳️ Requirements

• Demonstrated experience in delivering customer-facing AI features utilizing LLMs within production environments.

• Extensive hands-on experience in designing RAG systems and retrieval pipelines.

• Proficiency with embedding models, vector databases, chunking, hybrid search, and re-ranking techniques.

• Experience in building and maintaining evaluation frameworks for LLM-based systems.

• Strong capabilities in production-level, tested, and maintainable Python engineering.

• Background in creating APIs and data-retrieval pipelines that enhance context for AI systems.

• Ability to assess data quality, schemas, and retrieval architectures thoughtfully.

• Familiarity with agentic system patterns, tool utilization, multi-step orchestration, and error management in LLM workflows.

• Knowledge of AWS or GCP.

• Willingness to contribute to Kotlin components within a polyglot platform.

• Strong product instincts and a user-centered approach to development.

• Understanding of LLMOps, data retrieval strategies, prompt and context engineering, and production model evaluations.

• Capability to clearly communicate AI trade-offs to non-technical stakeholders.

• Valid authorization to work in the specified country; Pleo cannot provide visa sponsorship.

• Applications must be submitted in English.

🏝️ Benefits

• Your own Pleo card (no more personal expenses!)

• Catered meals or a lunch allowance based on your local office.

• Comprehensive private healthcare, with coverage options varying by location.

• 25 days of vacation in addition to public holidays.

• Options for hybrid or fully remote work arrangements.

• Complimentary mental health and well-being support through MyndUp.

• Paid parental leave.

• Opportunities for career development through larger projects, leadership roles, and skill acquisition.