AI Engineer II

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.

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

We're looking for an AI Engineer II to design and ship internal AI-powered tools end-to-end. You'll own AI-powered applications, workflow automations, and integrations from concept through production, evaluating and integrating new AI capabilities as you go. This is a hands‑on building role: you'll write production code, not just prototype it, while partnering with business stakeholders and growing into fuller ownership at the next level.

• Design and build internal AI-powered tools and web applications end-to-end, including front-end, back-end, data, API, and LLM/AI integrations.
• Own AI applications, workflow automations, and systems integrations from requirements gathering and technical design through production deployment and iteration.
• Partner with Sales Operations, Revenue Analytics, and cross-functional stakeholders to translate business problems into scalable technical solutions that deliver measurable value.
• Evaluate and integrate new AI models, APIs, frameworks, and development approaches based on business needs, technical feasibility, and performance.
• Develop production‑quality applications with appropriate testing, documentation, monitoring, and maintainability; troubleshoot and improve solutions post‑launch based on user feedback and performance.
• Build reusable AI capabilities, integrations, documentation, and development patterns that can be leveraged across teams and use cases.
• Communicate technical concepts, solution designs, tradeoffs, and outcomes to technical and non‑technical stakeholders, including presenting work to cross‑functional audiences.

1–2 years of hands‑on experience building software, data products, or AI‑powered tools through professional, internship, academic, or substantial independent project experience. Strong proficiency in Python and SQL, with experience in data analysis, application development, and statistical or machine‑learning workflows. Hands‑on experience with machine learning and statistical modeling, including regression, classification, feature engineering, and model evaluation. Experience working with large structured datasets using Snowflake, relational databases, or comparable cloud data platforms.

Experience developing or integrating REST APIs and backend services using FastAPI or similar frameworks, along with familiarity with modern web application development. Demonstrated ability to ship functional tools or applications to real users and evaluate their performance using appropriate technical or quantitative measures. Strong problem‑solving, communication, and collaboration skills, including the ability to learn unfamiliar technologies, incorporate stakeholder feedback, and explain technical tradeoffs to non‑technical audiences.

• Developing applications using LLMs, RAG,…