Senior Software Engineer - AI Integration
Indexed description
What You'll Do
In this role, you'll design and ship the systems that connect LLMs to real security workflows — from RAG pipelines over threat intelligence to agentic automation that handles triage and investigation steps that currently require human effort. You'll influence our AI architecture, product direction, and the standard for how the team builds with LLMs going forward.
- Design and build AI-powered workflows that serve both internal analysts and external customers across guided security operations
- Own the AI architecture end-to-end: model selection, prompt engineering, RAG pipelines, agent orchestration, and evaluation frameworks
- Optimize for cost and performance — manage token budgets, reduce latency, and build instrumentation so we know exactly what our AI spend buys us
- Collaborate with product and engineering to identify where AI creates real leverage and where it doesn't
- Mentor engineers on LLM best practices and raise the AI literacy of the broader team
- Engineering Principles: 5+ years of software engineering experience with strong fundamentals (you write production code, not just notebooks).
- AI/LLM Integration: Deep, practical experience using Agent Development Kit. You should have a proven track record of integrating LLMs into production environments - prompt engineering, context management, RAG architectures, agent frameworks, evaluation and observability.
- The Modern Stack: You are deeply proficient in React 18/19 and TypeScript. You are comfortable with React Router v7 and modern routing patterns.
- Data & Backend: You are comfortable designing schemas, writing queries, and reasoning about performance across PostgreSQL and Firestore. You feel at home with modern ORMs and use runtime validation to enforce data integrity at system boundaries.
- Security: Experience designing secure multi-tenant AI architectures — you understand how to build LLM integrations that enforce strict data isolation between customers.
- System Design: Strong understanding of scalable and highly available cloud-native system design.
- Product Focused: Experience working closely with product teams to ship user-facing features.
- Platform Orchestration: Knowledge of Infrastructure as Code (IaC) using Terraform to automate, orchestrate, and manage cloud platform resources effectively.
- Google Cloud Security: Familiarity or hands-on experience with Google Cloud Security products (e.g., Security Command Center, SecOps, , Mandiant).
- Advanced AI Workflows: Experience building autonomous AI agents, multi-modal applications, or complex prompt orchestration pipelines.
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