Security AI Technologist
Listed on 2026-07-24
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IT/Tech
AI Engineer (Applied/Software), Cybersecurity
Company Summary
Echo Star is reimagining the future of connectivity. Our business reach spans satellite television service, live‑streaming and on‑demand programming, smart home installation services, mobile plans and products. Today, our brands include Boost Mobile, DISH TV, Gen Mobile, Hughes and Sling TV.
Department SummaryOur Technology teams challenge the status quo and reimagine capabilities across industries. Whether through research and development, technology innovation or solution engineering, our team members play a vital role in connecting consumers with the products and platforms of tomorrow.
Job Duties and ResponsibilitiesCandidates must be willing to participate in at least one in‑person interview, which may include a live whiteboarding or technical assessment session.
Enterprise security infrastructure faces accelerating threats alongside rapid adoption of generative artificial intelligence technologies. This role addresses critical vulnerabilities, architectural gaps, and operational overhead by deploying secure Large Language Model platforms and automated threat workflows across the organization. The position resolves risk management challenges by establishing continuous monitoring, robust governance, and adversarial testing frameworks for artificial intelligence systems. Successful execution ensures robust defense mechanisms while safely enabling advanced automation across security operations.
WhatSuccess Looks Like
- Design, build, and operationalize secure Large Language Model‑driven platforms for security analytics, threat detection, third‑party risk management, and governance workflows
- Implement secure data ingestion and retrieval‑augmented generation pipelines across structured and unstructured security data sources to improve context retrieval and detection accuracy
- Develop agentic automation workflows that integrate directly into security tooling to augment security operations center analysts and threat hunters
- Establish continuous monitoring models to evaluate control effectiveness, risk scoring, detection correlation, model drift, and safety failures
- Define enterprise architecture and governance frameworks to protect artificial intelligence systems against prompt injection, unauthorized access, and adversarial abuse
- Lead threat intelligence and adversarial testing initiatives to defend against evolving artificial intelligence‑augmented tactics, techniques, and procedures
- Hands‑on technical expertise in building, integrating, and operating enterprise Large Language Model platforms and providers
- Deep understanding of Retrieval‑Augmented Generation architectures, embeddings, vector databases, tokenization, and contextual retrieval patterns
- Comprehensive knowledge of artificial intelligence security and risk frameworks, including NIST AI RMF, OWASP LLM Top 10, and MITRE ATLAS
- Proficiency in Python or equivalent languages for developing artificial intelligence pipelines, automation, and security tooling
- Critical experience securing cloud‑native systems and automated machine learning pipelines using defense‑in‑depth principles
- Artificial intelligence literacy and innovation capability to assess emerging adversarial threats, mitigate model risks, and drive secure technology adoption
- Familiarity with artificial intelligence governance, drift and safety monitoring, guardrails, and regulated or satellite/telecom security environments
- Minimum Education:
Bachelor’s Degree in Computer Science, Information Technology, related discipline, or commensurate industry experience - Minimum Experience:
3+ years of experience in Security Engineering, Security Architecture, Threat Research, or Detection Engineering; 3+ years in Generative AI development, modeling, integration, and security - Required Technical
Skills:
Must have at least 3 years of experience with:- Large Language Model platform integration (e.g., AWS Bedrock, Anthropic, Gemini, OpenAI)
- Python development for security tooling, pipelines, or automation
- AI security frameworks and threat modeling (NIST AI RMF, OWASP LLM Top 10, MITRE ATLAS)
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