AI Engineer - Quality and Post-Training

Glean is hiring an AI Engineer to improve the quality of its enterprise AI assistants and autonomous agents. The role uses evaluations, post-training, and production learnings to improve models, agent systems, and enterprise workflows in collaboration with product, platform, and research teams.

Responsibilities:

• Use eval results and production traces to improve the entire stack, including the agent harness, model routing, prompts, and retrieval, while weighing quality against latency and cost
• Work on post-training models with supervised fine-tuning (SFT) and preference- or reward-based optimization (e.g., DPO, PPO, GRPO), including generating the data for training
• Build RL environments for simulating enterprise workflows, including relevant evalsets, harness support, and LLM-based verifiers for hill-climbing and for internal and external benchmarking
• Improve the quality of representative evalsets, LLM judges and agentic verifiers, and calibrate them against human graders so the scores can be trusted in release decisions and model training
• Work with product, platform, and research teams across Glean to land quality improvements in production