Architect

Infor Inc.; Atlanta (GA); On-site; USD 140,000 - 200,000; Full time

Job summary

Infor Inc. is seeking an Software Architect to own the Gen AI Platform architectural direction, combining hands-on engineering with leadership to deliver cloud-native, scalable solutions.

You will define target architecture for agentic services, integrate LangChain/LangGraph, and collaborate with governance to ensure explainability, observability, and security across platforms.

Qualifications

• Experience architecting distributed, cloud-native systems in production environments.
• Hands-on coding experience in a technical architecture or engineering role.
• Experience with AI-assisted coding tools and LLM APIs.
• Proficiency in Python and evaluating front-end architecture (Angular).
• Working knowledge of AWS services (compute, serverless, containers, ML/AI).
• Exposure to agentic frameworks (LangChain, LangGraph).
• Experience directing technical direction across engineering teams.

Responsibilities

• Define target architecture for agentic services on AWS and modern web front ends.
• Write/review code, evaluate designs, prototype approaches for platform needs.
• Set integration standards for agentic frameworks in production services.
• Collaborate with governance to embed explainability, observability, and risk controls.
• Review designs for data flow, service boundaries, and security posture.
• Serve as escalation point for platform-level risks and architecture decisions.
• Collaborate across engineering, product, and governance teams for scalable Gen AI platform capabilities.

Skills

Cloud-native architecture

Hands-on coding

Python

Angular

AWS

LangChain/LangGraph

AI tool familiarity

Security posture

System architecture leadership

Tools

AWS

LangChain

LangGraph

Anthropic Claude API

Model Context Protocol (MCP)

OpenAI Codex

Claude Code

Angular

Python

Job description

Architect

Department: Development

Employment Type: Full Time

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.