Architect

Department: Development Location: Atlanta Description The Software Architect owns technical architecture for the Gen AI Platform, including design decisions that support agentic capabilities, governance features, and product integrations. This role combines hands-on engineering with technical leadership to guide scalable, cloud-native solutions across products. A Typical Day In The Life Includes Define target architecture for agentic services built on AWS, Anthropic Claude API/MCP, Python services, and Angular-based front ends. Write and review code, evaluate designs, and prototype technical approaches for complex platform needs. Establish standards for integrating agentic frameworks such as LangChain, LangGraph, or comparable tools into production services. Partner with AI Governance engineering to incorporate explainability, observability, and prevention capabilities into the platform architecture. Review technical designs from engineering teams and guide decisions related to data flow, service boundaries, and security posture. Serve as a technical escalation partner for platform-level risks and architecture decisions. Collaborate across engineering, product, and governance teams to support reliable, scalable, and responsible Gen AI platform capabilities. Basic Qualifications Experience architecting distributed, cloud-native systems in production environments. Experience writing and reviewing code in a hands-on technical architecture or engineering role. Experience using AI-assisted coding tools such as Claude Code, AWS Kiro, OpenAI Codex, or comparable tools. Experience with Python and ability to evaluate front-end architecture using Angular or comparable JavaScript frameworks. Working knowledge of AWS services, including compute, serverless, container orchestration, and managed ML/AI services. Exposure to agentic frameworks such as LangChain, LangGraph, or comparable frameworks. Experience setting technical direction across engineering teams or complex technical initiatives. Preferred Qualifications Experience architecting systems with governance, auditability, or explainability requirements. Familiarity with Anthropic Claude API and Model Context Protocol (MCP), or comparable LLM provider APIs and tool-use protocols. Experience designing services for reliability, cost efficiency, latency, and operational support. Experience guiding security, data flow, or service boundary decisions for platform services. Understanding of responsible AI practices, including evaluation of AI outputs and appropriate use of AI tools. Experience collaborating with product, governance, and engineering stakeholders on platform architecture. Experience supporting Gen AI, machine learning, or AI-enabled product capabilities in production environments. 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