Principal AI SOC Engineer

Description

Tyto Athene is hiring a Principal AI SOC Engineer to drive efficiency, velocity, and operational effectiveness across Security Operations Centers (SOCs) supporting federal missions. This is a hands‑on engineering role for someone who has deep SOC experience, has integrated SOC tooling, and knows how to transform analyst pain points into scalable, automated solutions.

The ideal candidate is a builder and leader, an engineer comfortable working across SIEM, SOAR, automation frameworks, and AI/ML platforms, with experience in Google Sec Ops considered a strong plus. This role blends technical execution with engineering leadership, including backlog grooming, solution design, delivery oversight, and active contributions to code, architecture, and team mentoring.

Responsibilities:

• Support design and engineer AI‑powered SOC capabilities that improve analyst efficiency, reduce alert fatigue, and accelerate detection and response.
• Partner with engineers and developers to deliver SOC and automation solutions, setting a high technical bar through hands‑on contribution and shared ownership.
• Apply AI/ML and GenAI techniques to SOC engineering problems, including alert enrichment, prioritization, correlation, and automated response.
• Build and evolve detection and response pipelines across SIEM, SOAR, EDR, and cloud security platforms.
• Engineer solutions across SIEM and SOAR platforms, including Elastic, Splunk, Azure or Sec Ops with a tool‑agnostic mindset.
• Integrate Google Sec Ops and GCP‑native services where appropriate to enhance detection, visibility, and response.
• Support design of scalable SOC architectures that support high‑volume telemetry and real‑time operational workflows.
• Build and maintain strong SOC automation using SOAR, custom services, and AI‑driven decisioning.
• Improve SOC velocity and throughput by automating repetitive analyst tasks and standardizing response patterns.
• Engineer workflows that translate detections into actionable, automated outcomes across security and infrastructure controls.
• Own and groom the engineering backlog; prioritize, design, and ship production‑ready solutions.
• Translate user stories and operational requirements into concrete technical designs and implementations.
• Set engineering standards and patterns for AI‑enabled SOC capabilities across the organization.

Required:

• 8–12 years of hands‑on experience in enterprise IT engineering, with expertise spanning cybersecurity, cloud platforms, Sec Ops, AI/ML, and emerging technologies.
• 3–5 years of direct SOC engineering experience, including designing, building, and optimizing SOC tooling, with at least 2 years supporting federal SOC environments (civilian agencies, DoD, Intelligence Community, or federal law enforcement).
• 3+ years of hands‑on experience applying AI/ML techniques to cybersecurity or operational systems, including building AI‑enabled security workflows for alert enrichment, triage, detection engineering, or automated response.
• 2+ years of practical experience working with LLMs or GenAI systems in production or near‑production environments, including RAG pipelines or LLM‑integrated automation for SOC use cases.
• Strong experience with SOC automation, orchestration, and playbook design, including API‑driven integrations and engineering detection, correlation, and response pipelines.
• Demonstrated ability to collaborate effectively with a team of engineers, setting technical strategy, reviewing designs, and fostering best practices in SOC, cloud, and AI/ML engineering initiatives.

Desired:

• Experience with Google Cloud Platform (GCP), including Google Sec Ops and Vertex AI for ML/GenAI use cases.
• Google Professional
  
  Certifications:
  
  Cloud Security Engineer, Cloud Security Architect, Machine Learning Engineer.

Clearance:

• SECRET clearance eligible (active clearance not required)

Location:

• Reston, VA (Hybrid)

Compensation:

• Compensation is unique to each candidate and relative to the skills and experience they bring to the position. This does not guarantee a specific salary as compensation is based upon multiple factors such as education, experience, certifications, and other requirements, and may…