Senior Software Engineer – AI​/Security Platform

• Design and build systems combining security-relevant data, detection signals, context, and foundation models to spot and predict active and impending 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
• Establish clear, measurable success criteria to evaluate iterations
• Architect and build a distributed platform correlating trillions of events and signals
• Synthesize events and signals into explainable findings and alerts for triage resolution agents
• Build a key capability of the Agentic SOC
• Collaborate with product and platform teams to co-design AI-enhanced threat detection and prediction workflows
• Contribute to the core architecture powering AI-native security operations and trusted enterprise automation at Splunk and Cisco

• Bachelor's Degree with 12+ years of related experience or Master's with 8+ years of related experience
• Understanding of security operations concepts, including attack surface management, threat analytics, detection, triage, investigation, and response
• Familiarity with endpoint logs, network traffic, authentication events, and cloud audit trails
• Experience implementing data platforms and/or data lakes and warehouses
• Experience building and maintaining pipelines for ingesting, parsing, and normalizing large-scale security telemetry
• Expertise in distributed systems design and implementation, emphasizing storage systems and storage access layers
• Consistent record building scalable backend services, APIs, and automation workflows in Python
• Proficiency 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
• Familiarity with TDIR/SIEM architectures, correlation searches, and threat hunting support systems
• Experience automating Sec Ops workflows and building scalable, resilient detection infrastructure
• Exposure to event storage systems or generating custom cybersecurity embeddings
• Hands‑on experience developing RAG and GraphRAG pipelines with databases such as FAISS or Pinecone
• Skill crafting, testing, and optimizing training workloads for large language or special‑purpose models such as GNNs, GCNs, and GATs
• Capability to design experiments evaluating model accuracy, usability, performance, and cost
• Background or interest in intuitive AI‑assisted analyst workflows focused on usability, trust, and decision support

Demonstrates expertise in designing and building distributed systems for security operations, with a strong focus on AI-enhanced threat detection and prediction. Proficient in developing scalable backend services and automation workflows, while collaborating effectively with cross-functional teams.

• Distributed Systems Design
• Python Backend Development
• CI/CD Pipeline Implementation
• Data Platform Development
• Threat Analytics and Response

• Security Operations Concepts
• Data Lakes and Warehouses
• Large-Scale Security Telemetry
• APIs and Automation Workflows
• Event Storage Systems
• RAG and GraphRAG Pipelines
• Training Workloads for Models
• Model Evaluation Experiments
• Threat Hunting Support Systems
• Agent Systems Design

• Collaboration with Product Managers
• Communication with Security SMEs
• Problem‑Solving in Security Context

• Attack Surface Management
• Threat Detection
• Triage and Investigation
• Cybersecurity Embeddings
• AI‑Assisted Analyst Workflows

• Git Hub
• Git Lab
• Jira
• Automated Testing Frameworks
• FAISS
• Pinecone