Senior Research Applied AI Engineer

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

About Us

Proofpoint is a global leader in human- and agent-centric cybersecurity. We protect how people, data, and AI agents connect across email, cloud, and collaboration tools. Over 80 of the Fortune 100, 10,000 large enterprises, and millions of smaller organizations trust Proofpoint to stop threats, prevent data loss, and build resilience across their people and AI workflows. Our mission is simple safeguard the digital world and empower people to work securely and confidently. Join us in our pursuit to defend data and protect people.

About Us

Proofpoint is a global leader in human- and agent-centric cybersecurity. We protect how people, data, and AI agents connect across email, cloud, and collaboration tools. Over 80 of the Fortune 100, 10,000 large enterprises, and millions of smaller organizations trust Proofpoint to stop threats, prevent data loss, and build resilience across their people and AI workflows. Our mission is simple safeguard the digital world and empower people to work securely and confidently. Join us in our pursuit to defend data and protect people.

How We Work

At Proofpoint you’ll be part of a global team that breaks barriers to redefine cybersecurity guided by our BRAVE core values

Bold

Responsive

Accountable

Visionary

Exceptional

The Role

AI is moving faster than any single product team can keep up with. For a security company, the hard question isn’t “can a model do this?” It’s which approach actually works, what it costs, how fast and reliable it is, and whether it’s worth building at all. That’s what this team answers. We’re an Applied AI Research team, and research is our product. We take important questions the company can’t yet answer and turn them into evidence people can act on.

As a Senior Applied AI Engineer, you’ll own a line of research from start to finish frame the question, build what’s needed to answer it, measure honestly, and reach a decision. When something is ready to move to another team, you’ll help them deploy it well, advising on the AI side and on how to monitor it once it’s live. Sometimes the answer is “this works, here’s the proof.” Sometimes it’s “this won’t work, and we found out in three weeks instead of six months.” Both count as success here.

What You'll Do

• Answer hard questions with evidence. Take a question nobody has answered yet. Make it testable, set a baseline, run the smallest experiment that settles it, and come back with an answer the company can act on.
• Build systems that improve themselves. A lot of our agentic work runs in long loops run an evaluation, study the results, produce a better version, run it again. You’ll build systems that improve on their own and recover when they go wrong.
• Make agent behavior measurable. Extend our evaluation platform so we can tell whether an agent is genuinely good - task suites, regression checks, and honest tradeoffs between quality, cost and speed. It’s something we build and maintain for the whole company.
• Work across hosted and self-hosted models. Most of what we do runs on third-party model APIs. We also serve open-weight models on our own GPUs and are pushing further into fine-tuning and efficient serving. You’ll help us work out which jobs suit which.
• Improve how we build with coding agents. We use coding agents every day and benchmark them against our own codebases. You’ll help our engineers get more out of them.
• Start from real problems. Spend time with stakeholders, understand their problems rather than collecting feature requests, and turn what you hear into research worth doing.
• Put working things in people’s hands. Build prototypes, playgrounds and APIs so stakeholders can try an idea themselves and learn alongside us. Often that’s how the decision gets made.
• Help get it into production. When something works, we don’t just hand it over. You’ll advise the team deploying it - on the AI side, and on how to monitor and understand the system once it’s running.
• Help the team get better. Mentor engineers, share what you learn, and help the team ask better questions.

What We're Looking For

• Bachelors, Masters or PhD in Computer Science or related field or equivalent experience
• 5+ years building software and ML systems, with recent hands‑on work on LLM systems that went past the prototype stage, 7+ years preferred.
• 3+ years of research experience (understanding customer problems and deriving/brainstorming solutions)
• Experience with Claude Code, Cursor or similar, used daily, without lowering your standard for correctness and tests.
• Experience in building and deeply evaluating agentic systems in production
• Experience with third‑party model APIs and open‑weight models (we run on our own GPU fleet)
• Strong Python and solid ML fundamentals
• Demonstrated expertise in AI evaluation, one of the most challenging and strategically important areas of modern artificial intelligence
• Familiarity with Kubernetes inference platform, Flyte for orchestration, LiteLLM / Langfuse and internal tooling for evaluation and tracing

Nice to Have

• Experience building open weights LLMs (not only classical (non‑LLM) ML models) and evaluating the system to quantify business value
• Experience fine‑tuning or serving open‑weight models
• Experience with automated prompt and pipeline optimization
• Experience with multi‑GPU serving and or MCP and tool protocols
• Previous cybersecurity experience such as phishing or threat detection
• Open‑source contributions or publications

Why Proofpoint?

• Competitive compensation
• Comprehensive benefits
• Career success on your terms
• Flexible work environment
• Annual wellness and community outreach days
• Always on recognition for your contributions
• Global collaboration and networking opportunities

Our Culture

Our culture is rooted in values that inspire belonging, empower purpose and drive success-every day, for everyone.

We encourage applications from individuals of all backgrounds, experiences, and perspectives. If you need accommodation during the application or interview process, please reach out to [e-mail].

Consistent with Proofpoint values and applicable law, we provide the following information to promote pay transparency and equity. Our compensation reflects the cost of labor across several U.S. geographic markets, and we pay differently based on those defined markets as set out below. Pay within these ranges varies and depends on job-related knowledge, skills, and experience. The actual offer will be based on the individual candidate. The range provided may represent a candidate range and may not reflect the full range for an individual tenured employee. This role may be eligible for variable compensation and/or equity. We offer a competitive benefits package, including flexible time off, a comprehensive well-being program with two paid Wellbeing Days and two paid Volunteer Days per year, plus a three-week Work from Anywhere option.

Base Pay Ranges

• SF Bay Area, New York City Metro Area
• Base Pay Range 200,300.00 - 293,810.00 USD
• California (excludes SF Bay Area), Colorado, Connecticut, Illinois, Washington DC Metro, Maryland, Massachusetts, New Jersey, Texas, Washington, Virginia, and Alaska
• Base Pay Range 167,300.00 - 245,355.00 USD
• All other cities and states excluding those listed above
• Base Pay Range 152,900.00 - 224,235.00 USD