Senior Applied AI Engineer
New
P
PleoSpend Management
We can hire on a remote, hybrid or in-person set-up in any of the locations listed on the advertFull-TimeSenior
Salary not disclosed
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Job Details
- Languages
- English
- Required Skills
- AWSPythonGCPKotlin
Requirements
- Proven experience shipping customer-facing AI features using LLMs into real production systems.
- Deep practical experience with RAG system design and retrieval pipelines (embedding models, vector databases, chunking, hybrid search, re-ranking).
- Experience building and operating evaluation frameworks for LLM-based systems.
- Strong Python engineering skills with production-grade, tested, and maintainable code.
- Experience building APIs and data retrieval pipelines feeding context into AI systems.
- Experience with agentic system patterns including tool use and multi-step orchestration.
- Familiarity with public cloud providers like AWS or GCP.
- Openness to contributing in a Kotlin stack as needed.
- Ability to explain AI trade-offs to non-technical stakeholders.
- Strong product instincts and ability to define problems from first principles.
Responsibilities
- Build and ship AI-powered product features for Pleo’s customers, owning outcomes end-to-end for a scoped area.
- Design and build end-to-end RAG systems for specific product use cases including chunking strategies, embedding model selection, retrieval optimisation, and quality evaluation.
- Own the full AI-product lifecycle covering prompt design, context/state management, agentic loops, output parsing, and deployment.
- Build evaluation datasets and automated eval pipelines to ensure AI feature quality.
- Instrument AI features for production observability, logging, drift detection, and quality monitoring.
- Collaborate with Product and Design to scope AI features from first principles.
- Partner with the GenAI Platform team to identify infrastructure needs and champion platform tooling.
- Support other engineers through code reviews, pairing, and pragmatic technical leadership.
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