Research Engineer

About the role

We’re hiring a Research Engineer to push Console’s core agent loop from powerful to truly self-improving. This role sits at the intersection of applied AI engineering and research.

Responsibilities

• Build the systems that let us measure, debug, and improve agent behavior in real-world conditions: production traces, offline replay, labeling workflows, eval harnesses, prompt and program optimization, and fine-tuning loops for high-volume agent tasks.
• One of your first major focus areas will be improving how Console’s agents reason over complex enterprise context. Using production traces, evals, assisted labeling, prompt/program optimization, and targeted model adaptation to make the system measurably better over time.
• Work closely with product, engineering, and leadership to ship improvements into production quickly, while helping define what research at Console looks like as we scale.

Who You Are

• A product-minded research engineer who enjoys building real systems people depend on.
• Strong technical background in software engineering, machine learning, or applied AI, demonstrated through an advanced degree and/or equivalent experience building production AI systems.
• Strong software engineering fundamentals and good judgment for designing, building, and debugging complex systems.
• Experience building evals for AI systems, including datasets, judges, metrics, offline replay, tracing, or regression testing.
• Practical understanding of modern model adaptation and post-training methods, including LoRA/QLoRA, SFT, distillation, preference optimization, reward modeling, DPO/GRPO, and reinforcement learning from verifiable feedback.
• Ownership mindset: you drive projects end-to-end, move quickly from real usage, and care about shipping measurable improvements.
• Enjoy following SOTA research into new models, agent architectures, evals, post-training methods, and optimization techniques.