AI Engineer II — Build Internal AI Tools & Automations

Proofpoint; Washington (District of Columbia); Híbrido; USD 84 000 - 147 000; Tempo integral

Vantagens oferecidas por esta oferta de emprego

Competitive compensation

Comprehensive benefits

Flexible work environment

Resumo da oferta

Proofpoint is seeking an AI Engineer II to design and ship internal AI-powered tools end-to-end. You’ll own AI applications, workflow automations, and integrations from concept through production, writing production code and partnering with business stakeholders.

This hands-on role requires strong Python/SQL and ML fundamentals, experience with large data, and the ability to deliver scalable, production-ready solutions that drive measurable value.

Qualificações

• 1–2 years hands-on software, data products, or AI tool experience.
• Strong Python and SQL proficiency with data analysis and ML workflows.
• Hands-on ML and statistical modeling experience.
• Experience with large structured datasets in cloud data platforms.
• Ability to ship production tools and measure performance.

Responsabilidades

• Design and build internal AI-powered tools and web apps end-to-end.
• Own AI apps, automations, and systems integrations from design to production.
• Collaborate with Sales Ops and Revenue Analytics to translate problems into scalable solutions.
• Evaluate new AI models, APIs, and frameworks for business benefit.
• Deliver production-quality apps with testing, docs, monitoring, and maintainability.
• Build reusable AI capabilities and patterns across teams.

Conhecimentos

Python

SQL

ML/AI

APIs (REST)

FastAPI

React/TypeScript

AWS

ETL/ELT

Snowflake

Data modeling

Ferramentas

Snowflake

Docker

AWS

FastAPI

REST APIs

Descrição da oferta de emprego

Proofpoint is seeking an AI Engineer II to design and ship internal AI-powered tools end-to-end. You’ll own AI applications, workflow automations, and integrations from concept through production, writing production code and partnering with business stakeholders.

This hands-on role requires strong Python/SQL and ML fundamentals, experience with large data, and the ability to deliver scalable, production-ready solutions that drive measurable value.