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 in how we dream and innovate

Responsive to feedback, challenges and opportunities

Accountable for results and best in class outcomes

Visionary in future focused problem-solving

Exceptional in execution and impact

The Role:

You’ll help turn Applied AI ideas into dependable software that gets used in the real world — by customers and by our internal threat analysts. Your work will help the team move faster (better tooling and workflows), keep results consistent and reproducible (evaluation and tracking), and help analysts self-serve through well-designed prompts, context, and tools.

You’ll be supported by senior engineers, but you’ll still ship meaningful work and see direct impact.

What you’ll do:

Build practical Python software
Create and improve backend components, libraries, and CLI tools used across our Applied AI Research workflows.

Help analysts self-serve LLM workflows
Partner with internal threat analysts to develop and maintain prompt/context patterns, guardrails, and templates — and help roll these into a self-serve setup using tools like Langfuse (or similar) for prompt management, tracing, and evaluation.

Contribute to productizing and deploying AI solutions
Work with senior engineers to move prototypes into production: packaging, integration, reliability, and deployment. You’ll take part in discussions about tradeoffs (speed vs. quality, cost vs. latency, build vs. buy) and learn how production decisions get made.

Support evaluation & reproducibility
Contribute to lightweight evaluation harnesses, experiment tracking, and documentation so we can repeat results and trust what we ship.

Use AI coding assistants thoughtfully
Use tools like Claude Code, Windsurf, Cursor (or similar) to accelerate development while keeping a high bar for correctness, readability, and tests.

What you bring:

(We know no one checks every box — this is our ideal list.)

1–2 years of experience in software development (or equivalent through internships + strong projects).

Good software fundamentals: clean code, debugging, data structures, basic design/architecture thinking.

Python, backend-leaning: comfortable writing small services, scripts, or CLI apps; familiarity with APIs and data handling.

Interest in applied AI: exposure to AI tooling/data pipelines/context building (coursework, projects, or on-the-job).

Hands-on with AI coding assistants: experience using at least one of Claude Code, Windsurf, Cursor, or similar.

Proof you like building: side projects, GitHub repos, demos, or hobby tools you can share.

Nice to have:

Interest in agentic AI (tool use, workflows, simple orchestration).

Familiarity with Docker, basic cloud concepts, or evaluation/observability tools.

Comfort collaborating with non-engineers (e.g., analysts) and translating needs into tooling.

How we’ll track progress:

In your first 3–12 months, we’ll look for:

Shipped improvements to our internal AI tooling (e.g., a CLI tool, pipeline step, evaluation feature, or reliability enhancement).

Analyst enablement: prompt/context patterns and a workflow that makes analysts faster and more consistent (with tracing/eval via Langfuse or similar).

Production contribution: you help deliver at least one AI feature/workflow into a production-like environment with guidance (and you can explain the tradeoffs we chose).

Growing ownership: you get faster at scoping work, asking good questions, and delivering maintainable code.

Why Proofpoint?

At Proofpoint, we believe that an exceptional career experience includes a comprehensive compensation and benefits package. Here are just a few reasons you’ll love working with us:

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 accessibility@proofpoint.com.

How to Apply

Interested? Submit your application along with any supporting information- we can’t wait to hear from you!

Software Engineer (AI)

Benefits

Job Description