Senior Software Engineer

• Design and build systems combining security-relevant data, detection signals, context, and foundation models to identify and predict threats
• Prototype and test AI features for decoding events and system environments and predicting anomalies and threats
• Work with security SMEs and security researchers to validate real-world utility
• Develop an AIDevOps pipeline for rapid experimentation with data, knowledge bases, models, and context memory
• Define clear, measurable success criteria to evaluate iterations
• Architect and build a distributed platform correlating trillions of events and signals into explainable findings and alerts
• Build capabilities for triage resolution agents in Cisco/Splunk’s Agentic SOC
• Collaborate with product and platform teams to co-design scalable AI-enhanced threat detection and prediction workflows
• Contribute to the core architecture powering AI-native security operations and trusted enterprise automation

• Bachelor's Degree with 7+ years of related experience or Master's with 4+ years of related experience
• Experience designing and implementing distributed systems, emphasizing storage systems and storage access layers
• Familiarity with data platforms, data lakes and warehouses, or streaming platforms
• Fluent Python or Go development experience building scalable backend services, APIs, and automation workflows
• Experience with CI/CD pipelines, Git Hub/Git Lab, Jira, and automated testing frameworks
• Experience designing agent systems that perform coding tasks
• Experience partnering with product managers, security SMEs, and engineers
• Preferred: experience building and maintaining pipelines for large-scale security telemetry
• Preferred: familiarity with TDIR/SIEM architectures, correlation searches, and threat hunting support systems
• Preferred: understanding of security operations concepts including attack surface management, threat analytics, detection, triage, investigation, and response
• Preferred: former Tier 3 SOC analyst or equivalent experience automating Sec Ops workflows and building scalable detection infrastructure
• Preferred: exposure to event storage systems or custom cybersecurity embeddings
• Preferred: hands-on RAG/GraphRAG pipelines and vector databases such as FAISS, Pinecone, or Weaviate
• Preferred: experience integrating and optimizing large language models or GNNs, GCNs, and GATs
• Preferred: experience shipping AI-powered features or products
• Preferred: ability to design model-output evaluation experiments for accuracy, usability, performance, and cost
• Preferred: background or interest in AI-assisted analyst workflows focused on usability, trust, and decision support

Demonstrates expertise in designing and implementing distributed systems, with a strong focus on security operations and AI-enhanced threat detection. Proficient in Python or Go for building scalable backend services and automation workflows, alongside experience in CI/CD pipelines and data platforms.

• Distributed Systems Design
• Python Development
• CI/CD Pipeline Implementation
• AI-Powered Feature Development
• Security Operations Concepts

• Distributed Systems
• Backend Services
• APIs
• Automation Workflows
• Data Platforms
• Storage Systems
• Threat Detection
• Model Evaluation
• Agent Systems
• Security Telemetry

• Collaboration
• Communication
• Problem-Solving
• Partnership

• Threat Analytics
• Attack Surface Management
• Detection
• Triage
• Investigation
• Response
• Security Operations Center
• Large Language Models
• GNNs
• GCNs

• Git Hub
• Git Lab
• Jira
• FAISS
• Pinecone
• Weaviate
• TDIR
• SIEM
• Automated Testing Frameworks
• RAG/GraphRAG Pipelines