What you’ll do
Build reference agentic applications on our platform — end-to-end examples of how agents should be designed, evaluated, deployed and monitored at Proofpoint.
Establish and document best practices: tool design and MCP integration, prompt and context management, memory and planning, cost/latency tradeoffs, failure recovery, and what "release-ready" means for a nondeterministic system.
Design evaluation harnesses — task suites, baselines, and quality, cost and latency metrics — and use them to decide what ships.
Turn ambiguous questions into working prototypes quickly, and present results to the teams who asked; recommend just as readily when an approach should be abandoned.
Harden successful prototypes into reusable platform capabilities that product teams can adopt.
Partner with experienced engineers, security researchers and product tech leads to go deep on the systems you build on.
Socialize agentic patterns across the company through demos, design reviews, written guides, and pairing sessions.
Communicate and understand stakeholders' requirements and participate in cross-team design discussions.
What we’re looking for
Bachelors or Master's Degree in Computer Science or a related field, or equivalent practical experience.
3+ years of engineering experience, with recent hands-on work on LLM or agentic systems that went past the prototype stage.
Good understanding of the agentic development lifecycle and its components - agent runtimes, tool and MCP integration, prompt and context management, memory, planning, orchestration, evals, tracing, guardrails, rollout and rollback.
Solid Python; TypeScript/Node a plus.
Experience working with globally distributed teams .
Experience building and running services in a cloud microservices environment — containers, CI/CD, automated deployment; AWS a plus.
Comfortable diagnosing distributed systems from traces and metrics; OpenTelemetry (including GenAI semantic conventions) a plus.
An eval-first mindset: measurement comes with the build, not after it.
Genuine enthusiasm for frontier AI — you already experiment with agent frameworks and LLM SDKs (LangGraph, Anthropic/OpenAI Agents SDK, MCP, LangChain or similar) and follow where the field is going.
Initiative and a bias toward shipping — you pick up ambiguous problems, get a PoC working and presented in days rather than quarters, and keep moving when the path isn't mapped out.
Fast learner with real curiosity — you want to know how the systems underneath you work, not just how to call them.
Preferred
Use of AI coding tools (Claude Code, Codex or similar) and familiarity with agent interoperability protocols such as MCP and A2A.
Building eval harnesses, benchmarks or ground-truth datasets.
Producing developer-facing reference implementations, SDK samples, or internal enablement material.
AG and semantic retrieval (vector stores, hybrid search), and working with both hosted APIs and open-weight models.
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!
