Senior Security AI Engineer

EchoStar•Littleton, CO

About The Position

The Senior Security AI Engineer will address enterprise security vulnerabilities, architectural gaps, and operational overhead by deploying secure Large Language Model platforms and automated threat workflows. The role establishes continuous monitoring, governance, and adversarial testing frameworks for artificial intelligence systems to strengthen defenses while enabling advanced security automation. The engineer will design, build, and operationalize LLM-driven platforms for security analytics, threat detection, third-party risk management, and governance. The position also develops secure data ingestion and retrieval-augmented generation pipelines, builds agentic automation integrated with security tooling, and implements monitoring, safeguards, and evaluation protocols for AI systems.

Requirements

Minimum of 3 years of experience in Security Engineering, Security Architecture, Threat Research, or Detection Engineering.
Minimum of 3 years of experience in generative AI development, modeling, integration, and security.
At least 3 years of experience integrating Large Language Model platforms, such as AWS Bedrock, Anthropic, Gemini, or OpenAI.
At least 3 years of Python development experience for security tooling, pipelines, or automation.
At least 3 years of experience with AI security frameworks and threat modeling, including NIST AI RMF, OWASP LLM Top 10, and MITRE ATLAS.
Strong technical expertise building, integrating, and operating enterprise LLM platforms and providers.
Deep understanding of RAG architectures, embeddings, vector databases, tokenization, and contextual retrieval patterns.
Comprehensive knowledge of AI security and risk frameworks, including NIST AI RMF, OWASP LLM Top 10, and MITRE ATLAS.
Ability to secure cloud-native systems and automated machine learning pipelines using defense-in-depth principles.
Bachelor’s degree in Computer Science, Information Technology, or a related discipline, or commensurate industry experience.
Willingness to participate in at least one in-person interview.

Nice To Haves

Familiarity with AI governance, drift and safety monitoring, and guardrails.
Familiarity with regulated or satellite/telecom security environments.

Responsibilities

Design, build, and operationalize secure LLM-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.
Develop agentic automation workflows integrated with security tooling to support security operations center analysts and threat hunters.
Establish continuous monitoring models for control effectiveness, risk scoring, detection correlation, model drift, and safety failures.
Build technical safeguards and controls aligned with enterprise architecture and governance frameworks to protect AI systems from prompt injection, unauthorized access, and adversarial abuse.
Implement adversarial testing routines and technical evaluation protocols to defend against evolving AI-augmented tactics, techniques, and procedures.
Assess emerging adversarial threats, evaluate model risks, and support secure technology adoption.