AI Automation Architect

Requirements:
12+ years in software engineering with strong depth across both development and quality engineering
4+ years as a hands-on principal architect or distinguished engineer with cross-org technical scope
Demonstrated experience designing quality infrastructure used at scale - 50+ engineers, high-velocity pipelines, enterprise SLAs
Direct production experience building or operating systems that incorporate LLMs or AI agents - not evaluations, but shipped systems
Background in large-scale CI/CD architecture and the performance engineering domain
Enterprise SaaS or platform engineering background; familiarity with regulated, high-uptime environments strongly preferred
Agentic AI & LLM Proficiency:
Deep, hands-on understanding of agentic AI patterns: tool use, multi-agent orchestration, planning loops, memory architectures, and human-in-the-loop design
Expert-level prompt engineering including chain-of-thought, few-shot, RAG, and structured output techniques applied to code and test generation
Experience designing evaluation harnesses for non-deterministic AI systems - statistical confidence, behavioral consistency, and regression detection
Familiarity with agent frameworks (LangChain, LlamaIndex, AutoGen, CrewAI, or equivalents) and their tradeoffs in production quality pipelines
Technical Depth:
Expert in Python and TypeScript; proficient in at least one compiled language (Java, Go, C#)
Deep knowledge of modern test frameworks across UI, API, and contract layers: Playwright, Stryker, pytest, REST Assured, Pact
Strong CI/CD architecture skills: Jenkins, GitHub Actions, pipeline-as-code, artifact management
Proficient with cloud-native infrastructure: Docker, Kubernetes, AWS, serverless execution environments