Join to apply for the Cyber AI & Automation Lead Engineer role at Tyto Athene, LLC
Responsibilities
- Design, develop, and implement AI/ML models to process high-volume, real-time streaming data from NOC/SOC sources.
- Perform advanced feature engineering on raw network and security data to extract indicators of compromise and behavioral anomalies.
- Develop and integrate data ingestion pipelines from SIEM, EDR, NDR, and network devices into the AI/ML ecosystem.
- Develop and deploy AI/ML models for anomaly detection in network traffic, user behavior, system logs, and security events.
- Engineer solutions to identify sophisticated cyber threats and network anomalies with high accuracy and low false positives.
- Design and build intelligent automation playbooks and workflows to automate incident response, network configuration changes, threat containment, and remediation actions.
- Develop predictive models to anticipate network failures, security breaches, or performance bottlenecks, enabling proactive intervention.
- Implement AIOps solutions to centralize monitoring, intelligently correlate events, and recommend or execute automated resolutions for common operational issues.
- Create and enhance SOAR integrations that are AI/ML-driven, optimizing triage, investigation, and response times.
- Focus on reducing MTTD and MTTR for network incidents and cyber threats through AI/ML-driven insights and automation.
- Automate repetitive, low-value tasks performed by NOC/SOC analysts, freeing them to focus on complex investigations, threat hunting, and strategic initiatives.
- Develop systems for intelligent alert prioritization to reduce alert fatigue and enable analysts to focus on critical events.
- Implement robust MLOps practices for continuous integration, delivery, and training of AI/ML models in production.
- Monitor model performance, detect drift, and ensure ongoing accuracy and relevance of deployed models.
- Establish clear data governance and lineage for AI/ML models, ensuring explainability and auditability.
- Collaborate with NOC engineers, SOC analysts, network architects, and cybersecurity experts to integrate AI/ML seamlessly into existing workflows.
- Translate complex AI/ML concepts and results into actionable insights for operational teams.
Required Qualifications
- 10+ years building and delivering solutions for U.S. federal government customers.
- Bachelor’s Degree in Engineering, Computer Science, or related field (equivalent experience considered).
- Expertise with open‑source LLMs (Llama, Gemma, Qwen) and VLMs (Phi4, Qwen‑VL) using Hugging Face.
- Strong prompt engineering skills.
- Experience building RAG pipelines with LangChain or LlamaIndex.
- Hands‑on Docker, Kubernetes, Helm; model serving with vLLM or Triton.
- ML observability tools and vector databases (Qdrant, Milvus).
- Familiarity with Model Context Protocol (MCP), BeeAI Framework, and secure, real‑time data access methodologies.
- Real‑time streaming processing experience (Kafka, Flink, Spark Streaming, Kinesis).
- Cloud‑native data platform experience (AWS Kinesis/MSK/S3, Azure Event Hubs/Data Lake, GCP Pub/Sub/BigQuery).
- Demonstrated NOC/SOC domain knowledge, network performance metrics, and cybersecurity concepts.
- Experience building automation scripts and integrating APIs for network and security tools.
- Agile and CI/CD practitioner with lean engineering practices.
- Strong analytical, problem‑solving, communication, and interpersonal skills.
- Knowledge of Go, Rust, or C++ for edge optimization.
- Active SECRET clearance required; highly desired.
Clearance
- Ability to obtain a Secret clearance is required; an active Secret clearance is highly desired.
Seniority Level
Mid‑Senior level
Employment Type
Full‑time
Job Function
Information Technology
Industries
Computer and Network Security and Technology, Information and Media