Architect

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.