Senior AI Engineer

Blee•San Francisco, CA

4d•Hybrid

About The Position

This is an AI Engineer role specializing in agent system design for someone who wants to architect and implement the next generation of intelligent compliance systems. You will design frameworks where multiple agents—powered by custom and foundational models—work together to surface, track, and explain compliance flags. You will also build and optimize applied AI/ML pipelines, work across model fine-tuning, prompt engineering, evaluation frameworks, and customer-specific AI configurations, and train models based on user feedback to provide more targeted compliance recommendations.

Requirements

5+ years of applied ML/AI engineering experience
Strong knowledge of agent-based architectures and orchestration frameworks
Strong Python; proficiency with modern software engineering practices (APIs, microservices, distributed systems)
ML frameworks (PyTorch, TensorFlow, Hugging Face)
LLM experience: fine-tuning, prompt engineering, RAG, evaluation
Background in data preprocessing, feature engineering, and training pipelines
Production ML: model serving, monitoring, A/B testing, data pipelines
Strong communication skills and ability to work cross-functionally

Nice To Haves

Based in the Bay Area or NY & willing to come into the office 3 days a week

Responsibilities

Architect multi-agent systems – Design and implement frameworks that integrate foundational LLMs and custom-trained models to power intelligent compliance workflows
Build and optimize AI/ML pipelines – Model fine-tuning, prompt engineering, and evaluation frameworks
Ensure explainability and traceability – Build mechanisms for transparent flagging, ensuring every compliance flag is traceable to prior rules, examples, or data assets
Automate compliance rule translation – Build systems that transform compliance rules into agent-ready logic paths
Design, train, and fine-tune models – Improve compliance accuracy and adaptability using user feedback and outcomes data to drive iterative training and personalization
Design model evaluation and monitoring infrastructure – Ensure reliability and auditability across customer deployments
Collaborate cross-functionally – Work with Product Engineers to integrate AI features via APIs, data pipelines, and frontend; partner with model training engineers to incorporate feedback loops into system design; collaborate with compliance users to translate complex rules into agent workflows
Stay current on AI/ML advances – Prototype and apply new techniques to our platform