Interested in this AI Software Engineer role at Proofpoint?
Apply Now →Skills & Technologies
About This Role
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
As a Staff Software Engineer on our Satori AI Platform team, you will drive the architecture of the internal platform that every Proofpoint product team uses to build agentic applications — spanning AI\-assisted development, evaluation\-based release gates, OpenTelemetry observability for agents in production, and cross\-product AuthX for AI workloads. Your direct users are fellow product engineers, and the products they ship protect business\-critical communications for Fortune 100 customers 24/7/365\. The patterns and primitives you set will define how mission\-critical agentic software ships across the company. This is a uniquely\-challenging role: we empower small teams to make large impacts, the systems are inherently non\-deterministic, and the bar for what we ship to product teams is high.
Your day\-to\-day
- Set architectural direction for one or more platform pillars: AI\-assisted developer workflows, eval\-driven release gates, OpenTelemetry for LLM/agent traffic, cross\-product AuthX, etc.
- Design agent runtimes and SDKs on frameworks like LangGraph, OpenAI Agents SDK, Anthropic's Agent SDK, and MCP, in Python (typed) and TypeScript/Node
- Define what "release\-ready" means for an agent at Proofpoint: the eval suites, safety checks, telemetry, and AuthX contracts that gate every rollout
- Partner with product team tech leads across the org to land your architecture in their stacks; turn one\-off integrations into reusable platform capabilities
- Drive the standards for prompt management, model selection, cost/latency budgets, and observability across products
Design, code, review, test, and deploy software features in our application stack — Staff engineers at Proofpoint still write code
- Mentor engineers across the platform and product teams; raise the company\-wide bar for what production agentic software looks like
What you bring to the team
- Experience developing and supporting AI\-powered applications, with exposure to agentic or LLM\-based systems in development, testing, or production environments.
- Proficiency in Python and/or TypeScript/Node.js, with the ability to write maintainable, scalable, and well\-tested code.
- Familiarity with agent frameworks such as LangGraph, LangChain, OpenAI/Anthropic Agents SDK, MCP, or similar technologies.
- Exposure to evaluation, monitoring, and observability concepts for AI applications, including experience with tools such as LangSmith, Braintrust, promptfoo, OpenTelemetry, or similar solutions.
- Experience troubleshooting application and service issues using logs, metrics, traces, and other diagnostic tools.
- Ability to collaborate effectively with engineering, product, and platform teams to deliver solutions and resolve technical challenges.
- Experience designing, developing, and supporting applications in cloud\-based and/or microservices environments.
- Strong written and verbal communication skills with the ability to clearly share ideas, provide updates, and participate in technical discussions.
- Demonstrated curiosity, attention to detail, and a willingness to learn new technologies and apply feedback.
- A proactive, team\-oriented mindset with a willingness to take ownership of assigned work and contribute to team success.
- B.S. or M.S. in Computer Science or a related field, or equivalent practical experience.
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!
Consistent with Proofpoint values and applicable law, we provide the following information to promote pay transparency and equity. Our compensation reflects the cost of labor across several U.S. geographic markets, and we pay differently based on those defined markets as set out below. Pay within these ranges varies and depends on job\-related knowledge, skills, and experience. The actual offer will be based on the individual candidate. The range provided may represent a candidate range and may not reflect the full range for an individual tenured employee. This role may be eligible for variable compensation and/or equity. We offer a competitive benefits package, including flexible time off, a comprehensive well\-being program with two paid Wellbeing Days and two paid Volunteer Days per year, plus a three\-week Work from Anywhere option.
Base Pay Ranges:
SF Bay Area, New York City Metro Area:
Base Pay Range: 136,200\.00 \- 214,005\.00 USD
California (excludes SF Bay Area), Colorado, Connecticut, Illinois, Washington DC Metro, Maryland, Massachusetts, New Jersey, Texas, Washington, Virginia, and Alaska:
Base Pay Range: 112,700\.00 \- 177,100\.00 USD
All other cities and states excluding those listed above:
Base Pay Range: 101,600\.00 \- 159,720\.00 USD
Salary Context
This $101K-$214K range is below the median for AI Software Engineer roles in our dataset (median: $183K across 194 roles with salary data).
Role Details
About This Role
AI Software Engineers build the applications and systems that AI models run inside. They own the API layers, data pipelines, frontend integrations, and infrastructure that turn a model into a product users interact with. Every AI company needs engineers who can build the software around the AI.
The challenge is building reliable systems around inherently unreliable components. Models are probabilistic. They'll give different answers to the same question. They hallucinate. They're slow. They're expensive. Your job is to build an application layer that handles all of this gracefully while delivering a product that users trust and enjoy.
Across the 3,708 AI roles we're tracking, AI Software Engineer positions make up 7% of the market. At Proofpoint, this role fits into their broader AI and engineering organization.
AI Software Engineer roles are among the most numerous in the AI job market. Every company deploying AI needs software engineers who understand AI integration patterns. The demand is broad, spanning startups to enterprises, across every industry adopting AI capabilities.
What the Work Looks Like
A typical week includes: building API endpoints that serve model inference with caching and fallback logic, designing the data pipeline that feeds context to a RAG system, implementing streaming responses in the frontend, debugging a race condition in the async inference pipeline, and optimizing database queries for the vector search layer. It's full-stack engineering with AI at the center.
AI Software Engineer roles are among the most numerous in the AI job market. Every company deploying AI needs software engineers who understand AI integration patterns. The demand is broad, spanning startups to enterprises, across every industry adopting AI capabilities.
Skills Required
Full-stack engineering skills with AI integration experience. Python and TypeScript are the most common requirements. You'll need to understand API design, database architecture, and how to build reliable systems around probabilistic outputs. Experience with streaming, async processing, and caching patterns is increasingly important as real-time AI applications proliferate.
Knowledge of vector databases, embedding APIs, and LLM integration patterns (function calling, structured outputs, retry logic) differentiates AI software engineers from general software engineers. Understanding cost optimization (caching strategies, model routing, batched inference) is valuable since inference costs can dominate application economics.
Strong postings describe the product you'll be building, the AI integration patterns you'll work with, and the scale requirements. Look for companies that have existing AI features and need engineers to improve and expand them, not companies that are 'planning to add AI' someday.
Compensation Benchmarks
AI Software Engineer roles pay a median of $219,250 based on 424 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $200,000. This role's midpoint ($157K) sits 28% below the category median. Disclosed range: $101K to $214K.
Across all AI roles, the market median is $217,500. Top-quartile compensation starts at $272,100. The 90th percentile reaches $325,000. For comparison, the highest-paying categories include AI Safety ($300,000) and Research Engineer ($280,000). By seniority level: Entry: $120,000; Mid: $200,000; Senior: $230,000; Director: $272,150; VP: $250,000.
Proofpoint AI Hiring
Proofpoint has 2 open AI roles right now. They're hiring across AI Software Engineer, AI/ML Engineer. Positions span Draper, UT, US, CA, US. Compensation range: $193K - $214K.
Location Context
Across all AI roles, 14% (508 positions) offer remote work, while 3,180 require on-site attendance. Top AI hiring metros: New York (1,045 roles, $220,000 median); San Francisco (810 roles, $277,088 median); Los Angeles (397 roles, $215,000 median).
Career Path
Common paths into AI Software Engineer roles include Software Engineer, Full-Stack Developer, Backend Engineer.
From here, career progression typically leads toward Staff Engineer, AI Architect, Engineering Manager.
If you're a software engineer, you're already 80% there. Learn the AI integration patterns: RAG, streaming inference, function calling, structured outputs. Build a project that demonstrates you can wrap an AI model in a production-quality application with proper error handling, caching, and user experience. That's the portfolio piece that gets you hired.
What to Expect in Interviews
Technical screens look like standard software engineering interviews with an AI twist. Expect system design questions about building reliable applications around probabilistic models: handling streaming responses, implementing retry logic for API failures, and designing caching strategies for LLM outputs. Coding rounds test standard algorithms plus practical integration patterns like async processing and rate limiting.
When evaluating opportunities: Strong postings describe the product you'll be building, the AI integration patterns you'll work with, and the scale requirements. Look for companies that have existing AI features and need engineers to improve and expand them, not companies that are 'planning to add AI' someday.
AI Hiring Overview
The AI job market has 3,708 open positions tracked in our dataset. By seniority: 102 entry-level, 1,705 mid-level, 1,469 senior, and 432 leadership roles (Director, VP, C-Level). Remote roles make up 14% of the market (508 positions). The remaining 3,180 roles require on-site or hybrid attendance.
The market median for AI roles is $217,500. Top-quartile compensation starts at $272,100. The 90th percentile reaches $325,000. Highest-paying categories: AI Safety ($300,000 median, 21 roles); Research Engineer ($280,000 median, 147 roles); AI Architect ($254,798 median, 67 roles).
AI Software Engineer roles are among the most numerous in the AI job market. Every company deploying AI needs software engineers who understand AI integration patterns. The demand is broad, spanning startups to enterprises, across every industry adopting AI capabilities.
The AI Job Market Today
The AI job market spans 3,708 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (2,605), Data Scientist (310), AI Software Engineer (259). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (102) are outnumbered by mid-level (1,705) and senior (1,469) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 432 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 14% of all AI roles (508 positions), with 3,180 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $217,500. Top-quartile roles start at $272,100, and the 90th percentile reaches $325,000. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Safety roles lead at $300,000 median, while Prompt Engineer roles sit at $140,000. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Python (1,890 postings), Aws (1,103 postings), Azure (877 postings), Rag (855 postings), Gcp (631 postings), Prompt Engineering (560 postings), Pytorch (545 postings), Claude (498 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
Get Weekly AI Career Intelligence
Salary data, skills demand, and market signals from 16,000+ AI job postings. Every Monday.