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.

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 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.

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.

Design and build AI‑driven workflow automations using enterprise‑grade orchestration platforms (e.g., Amazon Quick Automate, Unify Apps). 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.

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 vendors and clouds, and continuously evaluate the ensemble of AI tooling: LLMs (Anthropic, OpenAI, Amazon Bedrock, etc.)

and orchestration platforms (Amazon Quick Automate, Unify Apps, open‑source, and others). Stay ahead of the rapidly evolving AI landscape and proactively recommend where new models, frameworks, or techniques should be adopted.

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).

Build our first truly agentic CS applications—AI that completes work with minimal to no human intervention—starting with our long‑tail and smaller customer segments. Define the human‑in‑the‑loop guardrails, evaluation logic, and monitoring needed to operate agentic systems reliably and safely tinuously identify new opportunities across the long‑tail customer base where agentic AI can replace manual, repetitive work.

• Bachelor’s degree in Business, Computer Science, Engineering, or related field.
• 8+ years of professional experience, with at least 2+ years focused on AI technologies.
• Proven experience building AI applications…