Senior Applied AI Research Engineer - Cybersecurity

Proofpoint; Denver (CO); On-site; USD 160,000 - 225,000; Full time

Job summary

Proofpoint is seeking a Senior Applied AI Engineer to own a research line end‑to‑end, frame questions, build what’s needed to answer them, and measure results. You’ll help move successful work into production with guidance on AI and monitoring. This role emphasizes evidence and impact over theoretical work.

You’ll mentor engineers, collaborate across hosted and self‑hosted models, and push toward measurable improvements in efficiency and reliability. This is a dynamic, results‑driven environment.

Qualifications

• 5+ years building software and ML systems, including hands‑on work with LLMs beyond prototyping.
• 3+ years of research experience addressing customer problems and deriving solutions.
• Experience with third‑party model APIs and open‑weight models, and deploying to production.

Responsibilities

• Answer hard questions with evidence; design experiments, run baselines, and provide actionable results.
• Build self‑improving systems; run evaluations, iterate, and recover when things go wrong.
• Quantify agent behavior with evaluation platforms; balance quality, cost and speed.
• Collaborate across hosted and self‑hosted models; determine best fit for tasks.
• Improve development with coding agents; enable engineers to extract more value.
• Start from real problems; engage stakeholders and translate needs into research.
• Create prototypes, playgrounds and APIs so stakeholders test ideas and learn.
• Assist with production deployment; advise on AI aspects and monitoring post‑launch.
• Mentor engineers; share knowledge and help the team ask better questions.

Skills

Software development

ML systems

Python

AI evaluation

Kubernetes

Open‑weight models

Education

Bachelor's / Master's / PhD in Computer Science or related field

Tools

Claude Code

Cursor

Langfuse

LiteLLM

Flyte

Job description

Proofpoint is seeking a Senior Applied AI Engineer to own a research line end‑to‑end, frame questions, build what’s needed to answer them, and measure results. You’ll help move successful work into production with guidance on AI and monitoring. This role emphasizes evidence and impact over theoretical work.

You’ll mentor engineers, collaborate across hosted and self‑hosted models, and push toward measurable improvements in efficiency and reliability. This is a dynamic, results‑driven environment.