Sr Staff AI Engineer

Location: Santa Clara, California, United States; most teams work from the office full time.

Annual base salary: $163,200–$264,000.

Company

Cybersecurity organization building enterprise systems, infrastructure, and applications that support critical business workflows.

What you will do

• Set the architectural vision and technical direction for AI-first enterprise applications and platforms.
• Lead the architecture and delivery of complex cross-team systems spanning full-stack applications, cloud-native services, and applied AI.
• Establish reusable engineering standards, reference architectures, and shared capabilities for agentic workflows and RAG systems.
• Translate ambiguous, high-impact business problems into technical strategies and execution plans.
• Drive AI-native development workflows using tools such as Cursor and Claude Code.
• Mentor senior engineers and raise technical standards across the organization.

Requirements

• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field, or equivalent practical experience.
• At least 8 years of software engineering experience with technical leadership across complex production-scale systems.
• Deep expertise in full-stack and distributed systems engineering, APIs, enterprise data, system integration, cloud-native architecture, and production operations.
• Production experience building AI-integrated systems using LLMs, RAG, tool calling, and agentic workflows.
• Understanding of AI evaluation, guardrails, model reliability, security, latency, and production observability.
• Applicants must have current work authorization; new visa sponsorship and candidates in OPT/CPT status requiring future sponsorship are not currently considered. Existing H-1B transfers may be considered.

Nice to have

• Proficiency in TypeScript, Node.js/NestJS, React, Python, and SQL.
• Experience with vector databases, semantic search, context engineering, LangChain/LangGraph, MCP, A2A protocols, and production agentic architectures.
• Experience with LLM security controls, prompt-injection defenses, evaluation frameworks, and input/output validation.
• Experience with Docker, Kubernetes, event-driven systems, modern cloud infrastructure, or applied machine learning.
• Experience using Cursor, Claude Code, or Windsurf and building reusable enterprise platforms.

Culture & Benefits

• Work in a cybersecurity environment focused on innovation, collaboration, execution, integrity, and inclusion.
• Most teams collaborate from the office full time, with flexibility when needed.
• Compensation may include restricted stock units and a bonus.
• Employee benefits and reasonable accommodations are available.