Senior AI Engineer

Role overview Build production-ready AI capabilities within a Python backend, combining applied machine learning and LLMs with reliable service engineering. The work spans model integration, retrieval systems, background processing, and performance tuning, with a focus on practical user-facing outcomes rather than research alone.

Responsibilities - Design, implement, and deploy backend systems that incorporate language models and traditional machine learning. - Build and optimize vector database integrations for retrieval-augmented generation and other machine learning queries. - Develop maintainable, testable Python code and hybrid architectures that balance model calls with conventional ML approaches. - Tune backend and inference performance to reduce latency, including for compute-intensive models and parallel workloads. - Investigate issues across services, AI inference, and UI integration; identify root causes and implement targeted fixes. - Test backend and AI behavior before QA handoff, and work closely with product and engineering colleagues to deliver complete solutions.

Requirements - Three to five or more years of backend engineering experience with Python, FastAPI or Flask, and background job processing. - A master’s degree in a related field. - Evidence of deploying Python applications to production, with a solid grasp of software design patterns. - Applied machine learning experience, including training, evaluating, and maintaining task-specific models. - Knowledge of LLM integration, prompt design, and context-window optimization, with the ability to debug model behavior. - Experience with Celery or another major background-processing library, plus monitoring, error reporting, and testing of backend and AI components. - Strong understanding of backend performance, parallel processing, and multithreading; able to investigate problems independently.

Nice to have - Docker, continuous integration and delivery, deployment automation, or Kubernetes experience.

Benefits and work setup The position offers substantial autonomy on a small, fast-moving team, with the opportunity to shape AI architecture and engineering practices. A benefits package, time off, and holiday pay are provided.