Staff Software Engineer – AI/Security Platform

Jobtailor; San Francisco (CA); On-site; USD 170,000 - 260,000; Full time

Job summary

Jobtailor in San Francisco, CA seeks an experienced engineer to design and build AI-enhanced threat detection systems. You will integrate security data, signals, and context with foundation models to predict threats and decode events at scale.

You will prototype AI features, validate real-world utility with security SMEs, and craft an AI DevOps pipeline for rapid experimentation. The role targets SF’s high-demand AI security landscape.

Qualifications

• Bachelor's or Master's with required years of related experience.
• Designing distributed systems with storage layers and data platforms.
• Proficiency in Python for backend services and automation.
• Experience with CI/CD, GitHub/GitLab, and Jira.
• Experience with security telemetry sources and threat data.

Responsibilities

• Design and build systems combining security data, detection signals, and context.
• Prototype and test AI features for event decoding and threat prediction.
• Collaborate with security SMEs and researchers to validate utility.
• Develop an AI DevOps pipeline for rapid experimentation.
• Architect a distributed platform correlating trillions of events.
• Synthesize signals into explainable findings for triage agents.
• Collaborate with product and platform teams on scalable workflows.
• Contribute to AI-native security operations architecture.

Skills

Python development

Distributed systems

CI/CD Pipelines

Security telemetry sources

AI-powered feature integration

Education

Bachelor's degree + 8+ years

Master's degree + 6+ years

Tools

GitHub

GitLab

Jira

Splunk API

FAISS

Pinecone

Job description

• Design and build systems combining security data, detection signals, context, and foundation models to identify and predict threats
• Prototype and test AI features for event and system-environment decoding, anomaly prediction, and threat prediction
• Work with security SMEs and security researchers to validate real-world utility
• Develop an AI DevOps pipeline for rapid experimentation with knowledge bases, models, and context memory
• Define clear, measurable criteria for evaluating 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 scalable AI-enhanced threat detection and prediction workflows
• Contribute to the core architecture for AI-native security operations and trusted enterprise automation at Splunk and Cisco

Requirements

• Bachelor's Degree with 8+ years of related experience or Master's with 6+ years of related experience
• Experience designing and implementing distributed systems, with emphasis on storage systems and storage access layers
• Experience implementing data platforms and/or data lakes and warehouses
• Proficiency in Python development for scalable backend services, APIs, and automation workflows
• Experience with CI/CD pipelines, GitHub/GitLab, Jira, and automated testing frameworks
• Experience designing agent systems that perform coding tasks
• Experience partnering with product managers, security SMEs, and engineers
• Experience with security telemetry sources including endpoint logs, network traffic, authentication events, or cloud audit trails
• Preferred: Experience building and maintaining large-scale security telemetry ingestion, parsing, and normalization pipelines
• Preferred: Familiarity with TDIR/SIEM architectures, correlation searches, and threat-hunting support systems
• Preferred: Splunk API, internals, or platform development experience
• Preferred: Security operations knowledge including attack surface management, threat analytics, detection, triage, investigation, and response
• Preferred: Former Tier 3 SOC analyst or equivalent experience automating SecOps workflows and building scalable detection infrastructure
• Preferred: Event storage systems or custom cybersecurity embeddings experience
• Preferred: Hands-on RAG and GraphRAG pipeline development with databases such as FAISS or Pinecone
• Preferred: Experience crafting, testing, and optimizing workloads for large language models or GNNs, GCNs, and GATs
• Preferred: Experience shipping AI-powered features or products and integrating models into real-world workflows
• Preferred: Ability to design experiments evaluating model accuracy, usability, performance, and cost
• Preferred: Background or interest in intuitive AI-assisted analyst workflows focused on usability, trust, and decision support

Core Competencies

Demonstrates expertise in designing and implementing distributed systems, particularly in storage systems and data platforms. Proficient in Python development for scalable backend services and experienced in building AI-enhanced threat detection workflows.

Highest-signal resume keywords

• Distributed Systems Design
• Python Development
• CI/CD Pipelines
• Security Telemetry Sources
• AI-Powered Feature Integration

Hard Skills

• Distributed Systems
• Data Platforms
• Python
• APIs
• Automated Testing
• Security Telemetry
• Event Storage Systems
• Large Language Models
• Graph Neural Networks
• Threat Detection

Soft Skills

• Collaboration
• Communication
• Problem-Solving

Industry Keywords

• Security Operations
• Threat Analytics
• SIEM Architectures
• SOC Analyst
• Threat Prediction

Tools & Technologies

• GitHub
• GitLab
• Jira
• Splunk API
• FAISS
• Pinecone