CI&T
Tech / AI / Software
[28184]AI-AssistedModernisationEngineer
Neural analysis suggests this role is
optimal for Mid+ candidates.
“[28184] AI-Assisted Modernisation Engineer at CI&T. Skills: AI-Assisted Modernisation, LLM proficiency, Prompt Engineering, Automation QA. Leverage advanced AI tools, including large language models (LLMs) and autonomous agents, to transform traditional manual analysis and testing into a streamlined, automated process. Reverse-engineer requirements from existing codebases”
What You'll Achieve.
ensuring the highest standards of quality and performance for modernised systems; ensure alignment with business objectives
Industry & Context.
Critical Thinker
What They're Looking For.
Must Have
Deep understanding of software development, requirements elicitation, and QA methodologies, Hands-on experience using LLMs (e. g. , GPT-4, Claude 3. 5) for coding, analysis, or automation tasks, Ability to read and understand complex code structures in languages such as Java, C#, Python, or others relevant to legacy and modern systems, Familiarity with test automation principles and integration of AI-generated tests into continuous integration pipelines, Exceptional critical thinking skills to validate AI outputs and ensure comprehensive test coverage
Nice to Have
Familiarity with agentic frameworks (e. g. , LangChain, AutoGen, CrewAI) is a significant advantage
What You'll Do.
Leverage advanced AI tools
including large language models (LLMs) and autonomous agents
to transform traditional manual analysis and testing into a streamlined
Reverse-engineer requirements from existing codebases
Execute automated QA test cases
Deploy and orchestrate AI agents to analyse legacy codebases
extracting business logic and generating comprehensive
modern requirement documents through reverse engineering
Design prompts and agent workflows that automatically generate
and validate test cases against the modernised system
ensuring robust quality checks
Refine LLM prompts and manage agent frameworks to ensure high-accuracy outputs
minimising AI hallucinations in both requirements and test results
Manually validate generated requirements and test coverage to ensure alignment with business objectives
How You'll Work.
Team & 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
Full Job Description
## Description 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. ## About the Role 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. ## Key Responsibilities 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. ## Who You Are SDLC Master: Deep understanding of software development, r
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