Lead Cybersecurity, Application Security Architect, AI Models, Frameworks & Implementation

AT&T

Quick summary

Work type
On-site
Location
Alpharetta, GAAtlanta, GABedminster, NJBothell, WADallas, TXMiddletown, NJ
Salary
$128,400–$192,600 / yr
Posted
1 day ago
Nearby
99+ roles within 25 mi

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Salary context

Competitive pay

How this pay compares to similar roles

Similar $174k
This role $160k
$119k most similar roles pay here $214k

This role pays less than 58% of similar roles. Most pay $147,683–$199,475 — the shaded band above. At the midpoint, this role pays about $160k versus about $174k for comparable roles.

Based on 238 similar postings.

Employer

About AT&T

AT&T is a US-based telecommunications company providing wireless, broadband, and fiber internet service along with phone and connectivity products for consumers and businesses.

AT&T currently has 71 open roles on FindRole.

Listed pay typically runs $128,400–$192,600 across 67 roles with salary data.

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At a glance

TL;DR · Lead Cybersecurity, Application Security Architect, AI Models, Frameworks & Implementation

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We are seeking a Senior MLSecOps Engineer to join our cutting-edge team focused on developing and securing large language model (LLM) applications and agentic workflows. This role involves handling prompts, invoking models, and integrating plugins while addressing critical security issues such as prompt injection, jailbreaking, data poisoning, training-data leakage, and sensitive data exposure. The ideal candidate will have expertise in Python, JavaScript, and cloud platforms like AWS or GCP, along with a strong background in cybersecurity and AI ethics. This position requires an individual who can navigate complex technical challenges at scale, ensuring the robustness and security of our innovative AI products.

Skills

Python Go Docker CI/CD Prometheus Grafana Kubernetes Terraform AWS PostgreSQL LLM Agentic workflows Prompt handling Model invocation Plugin calling MLSecOps DevSecOps

What you'll do

  • Develop and implement security measures for LLM-based applications.
  • Handle prompts securely to prevent jailbreaking and data poisoning.
  • Monitor and mitigate risks of training-data leakage and sensitive data exposure.
  • Involve in the secure invocation of models and plugins within agentic workflows.
  • Conduct regular audits to ensure compliance with MLSecOps/DevSecOps practices.

What we're looking for

  • Experience in MLSecOps and DevSecOps for AI applications.
  • Proficient in handling prompts, invoking models, and calling plugins/tools.
  • Knowledge of security issues like prompt injection, jailbreaking, data poisoning.
  • Understanding of training-data leakage and sensitive data exposure prevention.
  • LLM-based application development and agentic workflow implementation skills.

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