AI Automation Engineer

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 We are looking for a high-performing AI Automation Engineer to join our CS Operations – GTM Automation & AI team. In this role, you will design, build, and continuously evolve the AI-driven applications and tools — chat assistants, workflow automations, and increasingly autonomous agents — that make our post-sales revenue-focused teams (Customer Success, Renewals, Technical Account Management, Managed Services) exponentially more effective and efficient.

You will partner closely with key stakeholders, end users, AI Integration, Data Engineering, and Enablement to turn ideas into high-impact AI capabilities.

This role is ideal for someone who is fiercely passionate about the pace of AI innovation, loves rolling up their sleeves, and is energized by rapidly evolving technologies and a fast-paced environment. You will be part of a fast-moving team that thrives on working with rapidly evolving technologies to deliver value to end-users and our customers.

This an individual contributor role reporting to the leader of the GTM Systems & Automation pillar, which in addition to AI is responsible for the full CS tech stack.

Your day to day AI Chat Assistants & Conversational AI

• Evolve our role-based AI chat assistants — trained to answer questions and take actions tailored to specific personas (e.g., CSM, Renewals).
• Apply advanced prompt engineering techniques to construct the right level of context, ensuring accurate analysis and reliable output.
• Continuously test, monitor, and refine assistant performance based on usage data and user feedback.

AI-Driven Workflow Automation

• Design and build AI-driven workflow automations using enterprise-grade orchestration platforms (e.g., Amazon Quick Automate, UnifyApps).
• Use AI to process data, apply evaluation and decision logic, generate outputs, and trigger downstream actions.
• Deploy scheduled and trigger-based workflows, and design human-in-the-loop checkpoints where judgment or approval is required.

AI Architecture & Optimization

• Continuously optimize AI system performance — faster data retrieval and analysis, breaking workflows into modular AI agent building blocks, and determining what belongs in a natural-language prompt versus what should be engineered in code (e.g., Python).
• Assess which AI logic should live at which layer — what should be centralized versus decentralized across different vendors and clouds — and continuously evaluate the ensemble of AI tooling LLMs (Anthropic, OpenAI, Amazon Bedrock, etc.) and orchestration platforms (Amazon Quick Automate, UnifyApps, open source, and others).
• Stay ahead of the rapidly evolving AI landscape and proactively recommend where new models, frameworks, or techniques should be adopted.

AI Integration

• Partner closely with the AI Integration and Data teams to expand the AI “brain” — extending data access and connectivity via MCP (Model Context Protocol) and connecting to additional datasets in our data warehouse.
• Integrate and wire together our AI capabilities (chat, headless, workflow) with the broader CS tech stack, including Salesforce, Gainsight/Totango, Clari, Gong, Pendo, Snowflake/Redshift, AWS, and Power BI.
• Help determine what AI processing we build and own ourselves versus what we leverage from point-solution vendors (e.g., Salesforce, Gong, Totango).

Agentic AI Applications

• Build our first truly agentic CS applications — AI that completes work with minimal to no human interventio…