AI Software Engineer, Security

Everpure•Santa Clara, CA

19h•$149,000 - $224,000•Onsite

About The Position

As a Security-Focused AI Software Engineer on our Digital Product and AI Platform team, you will champion secure-by-design principles to safeguard production backend microservices and cutting-edge AI architectures. Collaborating closely with engineering, product management, cloud infrastructure, and security teams, you will architect, build, and operate resilient systems that power enterprise AI capabilities. By embedding automated security controls, threat modeling, and proactive vulnerability management directly into the development lifecycle, you will ensure our digital platform remains performant, trustworthy, and protected at scale.

Requirements

Strong engineering proficiency in Python, RESTful microservices, and deploying cloud-native applications within AWS environments (including containerized architectures).
Proven skill in threat modeling, secure API design, cryptography fundamentals, data protection, secrets management, and applying OWASP/supply-chain risk mitigations.
Hands-on experience developing LLM-driven or Agentic AI applications, RAG pipelines, prompt engineering strategies, and production guardrails or model evaluation frameworks.

Responsibilities

Drive Application Security & Secure SDLC: Champion end-to-end security practices across the engineering team by conducting threat modeling, secure design reviews, and vulnerability remediations, ensuring all digital products and APIs adhere to least-privilege, robust authentication, and strict data protection standards.
Architect Secure AI & Microservices: Design, build, and deploy production-grade backend services and Agentic AI workflows in Python on AWS, integrating LLMs, retrieval-augmented generation (RAG) pipelines, and microservices with enterprise platforms.
Establish AI Guardrails & Governance: Implement safeguards—including output validation, automated prompt testing, fallback mechanisms, rate limiting, and human-in-the-loop workflows—to ensure reliable, deterministic, and safe AI behavior in production environments.
Elevate System Observability & Incident Readiness: Build monitoring, audit logging, and automated evaluation frameworks to proactively identify security signals, supporting rapid incident response and driving continuously improved engineering practices.