Live opening · Posted 1 day ago
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About the role
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As part of the Digital Quality Engineering team, this role will focus on driving innovation through AI-led quality engineering practices. The engineer will be responsible for designing and developing scalable AI agent ecosystems, including MCP servers, RAG-based agents, and intelligent automation solutions built on AWS Bedrock and modern LLM frameworks.
This role plays a key part in transforming traditional QA into an AI-powered quality engineering function, enabling proactive defect prevention, intelligent test generation, and autonomous validation systems. You will work closely with product, engineering, and quality teams to embed AI capabilities across the SDLC and accelerate delivery with high quality.
Responsibilities:
Demonstrated experience using AWS AI/ML services such as Amazon SageMaker, Bedrock, and AgentCore.
Demonstrated experience using AI-assisted development tools (e. g., GitHub Copilot, Claude, Kiro) to accomplish tasks such as generating and reviewing code, writing and maintaining tests, creating documentation, and debugging, while exercising sound judgment to validate and take ownership of AI-generated output.
Understanding of prompt engineering, AI workflows, and/or model integration patterns.
Design and develop MCP servers and AI agent frameworks to support scalable and reusable AI-driven solutions.
Build and deploy RAG-based agents and intelligent workflows leveraging AWS Bedrock and LLM ecosystems.
Drive adoption of AI-powered quality engineering practices, including test generation, validation, and defect prediction.
Develop end-to-end solutions combining AI/ML, backend services, and frontend interfaces (full-stack ownership).
Integrate AI agents with existing automation frameworks and enterprise systems.
Collaborate with cross-functional teams to identify opportunities for AI-driven optimisation in QA processes.
Ensure production-grade deployment, monitoring, and performance optimisation of AI systems.
Establish best practices, reusable components, and governance for AI/ML development within QE.
Mentor team members and promote a culture of AI innovation and experimentation.
Stay updated with emerging AI trends and proactively bring in new capabilities into the ecosystem.
Requirements:
Bachelor's degree in Computer Science, Engineering, Data Science, or related field.
4+ years of experience in AI/ML development, including building and deploying AI models and systems.
Hands-on experience with AWS Cloud services, especially Bedrock or similar LLM platforms.
Strong programming skills in Python/Java or similar languages.
Experience in building and deploying AI/ML solutions in production environments.
Understanding of LLMs, prompt engineering, NLP, or generative AI concepts.
Experience in full-stack development (frontend + backend integration).
Strong problem-solving skills with the ability to work in a collaborative Agile environment.
Behavioural Competencies:
Ability to produce high-quality results, work in a collaborative environment by embracing diverse perspectives and take a solution-based approach.
Adapt communication clearly and concisely based on team dynamics and express thoughts and ideas effectively.
Ability to engage effectively with peers and stakeholders to build trust and reliable working relationships.
Ability to understand business processes, implement innovative solutions, and guide juniors on continuous improvement by constantly updating oneself on current technology and trends.
Inquisitive to understand customer and business expectations while creating value addition on technical solutions.
Experience
4-7 yrs
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