[28184] AI-Assisted Modernisation Engineer

BrisbaneFull Timemid

OtherEngineer

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Quick Summary

Overview

At CI&T, we're redefining the future of digital experiences with the power of AI technology. We are on the lookout for a highly technical, AI-forward professional to drive a major legacy migration and modernisation project, combining the best of business analysis and automation quality assurance.

Technical Tools

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As an AI-Assisted Modernisation Engineer, you will leverage advanced AI tools, including large language models (LLMs) and autonomous agents, to transform traditional manual analysis and testing into a streamlined, automated process. Your primary focus will be on reverse-engineering requirements from our existing codebase and executing automated QA test cases, ensuring the highest standards of quality and performance for modernised systems.

This is an unique position combining the strategic insights of a Business Analyst with the precision and quality assurance of an Automation QA.

AI-Driven Business Analysis: Deploy and orchestrate AI agents to analyse legacy codebases, extracting business logic and generating comprehensive, modern requirement documents through reverse engineering.

AI-Driven Quality Assurance: Design prompts and agent workflows that automatically generate, execute, and validate test cases against the modernised system, ensuring robust quality checks.

Prompt Engineering & Orchestration: Refine LLM prompts and manage agent frameworks to ensure high-accuracy outputs, minimising AI hallucinations in both requirements and test results.

Validation & Human-in-the-Loop: Act as the critical bridge between AI output and reality, manually validating generated requirements and test coverage to ensure alignment with business objectives.

Collaboration: Work closely with cross-functional teams, including developers, Scrum Masters, and QA specialists, to ensure seamless integration of AI-driven processes into the software development lifecycle.

SDLC Master: Deep understanding of software development, requirements elicitation, and QA methodologies.

AI/LLM Proficiency: Hands-on experience using LLMs (e.g., GPT-4, Claude 3.5) for coding, analysis, or automation tasks. Familiarity with agentic frameworks (e.g., LangChain, AutoGen, CrewAI) is a significant advantage.

Code Literate: Ability to read and understand complex code structures in languages such as Java, C#, Python, or others relevant to legacy and modern systems.

QA Automation Expert: Familiarity with test automation principles and integration of AI-generated tests into continuous integration pipelines.

Critical Thinker: Exceptional critical thinking skills to validate AI outputs and ensure comprehensive test coverage.