below marketmost similar roles pay hereabove market
This role pays less than
65%
of similar roles. Most pay
$129,925–$181,337
— the blue band above.
At the midpoint, this role pays about
$143k
versus about
$156k
for comparable roles.
Based on 240 similar postings.
Employer
About Proofpoint
Proofpoint is a cybersecurity company specializing in email security, threat protection, data loss prevention, and compliance. Privately held by Thoma Bravo since 2021, it serves over 500,000 organizations including 87 of the Fortune 100.
Proofpoint currently has
10 open roles
on FindRole.
Listed pay typically runs
$136,200–$214,005
across 6 roles with salary data.
The AI Engineer II joins the Revenue Analytics team to design and ship internal AI-powered tools and web applications end-to-end. This hands-on role involves owning applications, workflow automations, and systems integrations from requirements gathering through production deployment. You will build production-quality code, evaluate new AI models, and develop reusable capabilities to solve business problems for Sales Operations and Revenue Analytics. Key technical requirements include proficiency in Python, SQL, and machine learning workflows like regression and classification. You will work with large structured datasets in Snowflake, develop REST APIs using FastAPI, and integrate LLMs, RAG, and vector search. Preferred skills include React, TypeScript, Docker, and AWS. The role focuses on translating complex business needs into scalable technical solutions and measurable outcomes within a cybersecurity context.
What does a AI Engineer earn?
Median $211200 from 126 postings across 36 companies.
Design and build internal AI-powered tools and web applications from front-end to back-end.
Own AI applications and workflow automations from requirements gathering through production deployment.
Translate business problems from stakeholders into scalable technical solutions and measurable value.
Evaluate and integrate new AI models, APIs, and frameworks based on technical feasibility.
Develop production-quality code including testing, documentation, monitoring, and post-launch troubleshooting.
Build reusable AI capabilities, integrations, and development patterns for cross-team use.
Communicate technical concepts, solution designs, and tradeoffs to both technical and non-technical audiences.
What we're looking for
1–2 years of experience building software, data products, or AI-powered tools through professional, internship, academic, or substantial independent project experience.
Strong proficiency in Python and SQL for data analysis, application development, and 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.
Demonstrated ability to ship functional tools to real users and evaluate performance using technical or quantitative measures.
Experience developing applications using LLMs, RAG, embeddings, prompt engineering, and LLM APIs (preferred).
Experience with React, TypeScript, Docker, AWS, or ETL/ELT pipelines (preferred).