AI Solutions Architect (LLM & Enterprise AI)

Quick Facts

• Role: AI Champion (enterprise AI solutions)

• Focus: Generative AI for large ERP product ecosystems

• Scope: Strategy, prototyping, implementation, and AI adoption across the full SDLC

Description

You will co-create and execute an AI strategy for an ERP product family, turning experiments and proofs of concept into solutions used in everyday engineering and operations. The role designs and implements LLM-based solutions (including AI agents and RAG) while finding practical ways to apply AI to large codebases, testing, deployment, and system maintenance. You will also help establish safe, responsible AI usage and grow internal AI capabilities through mentoring and standards.

Responsibilities

• Identify business and technological areas with the highest AI potential

• Coordinate AI initiatives across the entire software lifecycle (requirements, development, testing, deployment, maintenance, and DevOps support)

• Design and implement solutions using LLMs, AI Agents, and RAG

• Develop approaches for analyzing and indexing very large code repositories and delivering relevant context to AI models

• Apply AI to software engineering tasks: code analysis, code generation/modification, code review, refactoring, and documentation support

• Automate and improve testing using AI (test case generation, result analysis, regression/error identification)

• Explore AI for implementation and deployment workflows (requirements analysis, system configuration, data migration, documentation)

• Use AI in operations/maintenance (incident analysis and increasing first-line support automation)

• Build AI mechanisms for monitoring legal/regulatory changes and assessing their impact

• Transform team processes using AI (skills development, knowledge management, documentation, and CI/CD)

• Create proof of concept prototypes and evaluate models/frameworks/platforms

• Define AI solution architecture and integration with existing code repositories, knowledge bases, and tooling

• Collaborate with architects, developers, testers, consultants, maintenance teams, and product/business owners

• Promote AI adoption via knowledge sharing, mentoring, workshops, standards, and best practices

• Monitor AI technology trends and convert them into business value

• Define guidelines for secure and responsible enterprise AI usage (information security, IP protection, quality of outputs)

Benefits

• Opportunity to actively shape and scale AI-driven ideas with real business impact

• Support from leaders with an emphasis on work-life balance and continuous skill development

• Culture focused on responsibility, teamwork, respect, and belonging

• Ability to grow career potential with access to broad industry and technology knowledge