Job Description

About Gadriel

Gadriel is the AI System Assurance company. AI is now writing code, making decisions, and running inside production systems, and most teams can't prove any of it works before it ships. We validate what AI writes, what AI does, and what it's deployed into, before release. Our founders have 25 years in enterprise cybersecurity and hold three USPTO patents. We're building the validation layer that teams will need for every AI system they deploy.

The role

We're hiring a Backend Engineer to build the core validation engines and services behind our products. You'll work on deterministic, reproducible validation: the same input gives the same result every time. This is systems work, not prompt wrangling.

What you'll do

• Design and build backend services and analysis engines that validate AI-generated code and AI system behavior
• Implement validation techniques that are mathematically grounded and reproducible, not "LLM-as-judge"
• Build high-throughput, reliable pipelines that run locally, in CI/CD, and in customer environments
• Integrate with AI coding tools, agent frameworks, and enterprise systems
• Own services end to end, from design through production
• Work directly with the founders and shape the architecture

What we're looking for

• Strong backend engineering skills in Python, Go, or C++ . Deep in one is enough; we don't need all three.
• Solid fundamentals: distributed systems, APIs, concurrency, performance, testing
• A working understanding of AI concepts: LLMs, agents, RAG, embeddings, and how these systems fail
• Comfort reading and reasoning about code you didn't write
• Ownership. You ship, you measure, you fix.

Nice to have

• Experience with static analysis, security tooling, or developer tools
• Familiarity with agent protocols such as MCP
• Background in applied math, statistics, or information theory
• Experience in a startup or early-stage environment

Why Gadriel

• Real technical depth in a new category
• Founder-led team with enterprise credibility and patented IP
• Fully remote
• Early-team ownership and influence
• Compensation: [range] + [equity]

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