📍 Location: Bandar Baru Klang (Hybrid)

🏢 Company: SRKK Group

🎓 Employment Type: Internship

🎯 Position: AI Product Engineer Intern

✨ We are looking for interns who are humble, hungry, and smart.

Build, Experiment, and Ship the Next Generation of AI Products

SRKK Group is a leading end-to-end digital transformation consultancy with established presences in Malaysia and Singapore. As a Microsoft-focused technology organization, we help businesses modernize and innovate through cloud, data, artificial intelligence, cybersecurity, business applications, and the modern workplace.

We are seeking a technically capable and product-minded AI Product Engineer Intern to help build AI-powered applications, copilots, intelligent agents, and reusable product accelerators.

This internship is ideal for students or recent graduates who already have practical programming experience and are excited about turning emerging AI technologies into working products. You will contribute across the development lifecycle, including prototyping, software engineering, data integration, testing, deployment, monitoring, and customer demonstrations.

You will work with technologies such as Python, Azure AI, Azure OpenAI, Microsoft Fabric, Large Language Models, AI agents, Retrieval-Augmented Generation, vector databases, APIs, and agentic coding tools to develop AI solutions that address real business challenges.

💼 What You’ll Do

AI Application & Agent Development

• Design, develop, and test AI-powered applications, copilots, and intelligent agents.
• Build AI capabilities using:
  • Azure AI
  • Azure OpenAI
  • OpenAI models
  • Microsoft Fabric
  • Large Language Models
  • AI agent frameworks
  • Other relevant AI platforms
• Implement new product features and improve existing AI capabilities.
• Develop intelligent workflows that automate tasks, retrieve information, and support business decision-making.
• Test AI outputs for functionality, relevance, accuracy, and reliability.

Rapid Prototyping & Idea Validation

• Rapidly develop:
  • Minimum Viable Products
  • Proofs of Concept
  • Technical Demonstrations
  • Reusable AI Accelerators
• Experiment with emerging AI models, development frameworks, and agent orchestration approaches.
• Evaluate the technical feasibility and potential business value of new AI ideas.
• Gather feedback from internal teams and customers to improve prototypes.
• Convert successful prototypes into more reliable and scalable product features.

RAG & Enterprise Knowledge Solutions

• Support the development of Retrieval-Augmented Generation (RAG) solutions.
• Connect AI applications to structured and unstructured enterprise information.
• Work with:
  • Vector databases
  • Embeddings
  • Semantic search
  • Enterprise knowledge sources
  • Document repositories
  • Databases
• Assist in designing document ingestion, chunking, indexing, retrieval, and response-generation workflows.
• Test retrieval quality and improve how AI applications identify and use relevant information.
• Support the responsible handling of customer and organizational data.

Data & Knowledge Integration

• Integrate AI applications with:
  • Microsoft Fabric
  • SQL databases
  • Data pipelines
  • Semantic models
  • APIs
  • Documents and knowledge repositories
• Prepare and transform data for use in AI applications.
• Support data ingestion, validation, and integration activities.
• Work with data and engineering teams to ensure reliable access to required information.
• Help troubleshoot issues involving data availability, data quality, and AI retrieval performance.

Product Engineering

• Contribute to front-end, back-end, API, and workflow development.
• Build reusable and maintainable software components.
• Apply software engineering principles across:
  • Object-oriented programming
  • API development
  • Code organization
  • Testing
  • Debugging
  • Version control
• Participate in peer reviews and improve code based on technical feedback.
• Document product features, architecture decisions, technical limitations, and implementation approaches.

API & System Integration

• Build and consume APIs that connect AI models, applications, databases, and enterprise systems.
• Support the integration of AI features into existing business applications and workflows.
• Test API responses, authentication flows, error handling, and application behavior.
• Assist in troubleshooting integration and connectivity issues.
• Maintain clear documentation for APIs and integration components.

Testing, Deployment & Monitoring

• Assist with functional testing, integration testing, debugging, and issue resolution.
• Support the deployment of AI applications into development, testing, and production environments.
• Monitor solution behavior and assist in identifying performance, quality, or reliability issues.
• Support the continuous improvement of deployed AI products.
• Help maintain test cases, technical records, release notes, and deployment documentation.
• Escalate risks, defects, and technical limitations to the relevant engineering team.

AI-Assisted & Agentic Development

• Use approved AI-assisted development tools to accelerate coding, testing, troubleshooting, documentation, and experimentation.
• Gain practical exposure to tools such as:
  • GitHub Copilot
  • Cursor
  • Claude Code
  • Windsurf
  • Similar agentic coding platforms
• Review, test, and validate AI-generated code before incorporating it into a solution.
• Apply secure coding, data protection, confidentiality, and responsible AI practices when using development assistants.
• Evaluate where agentic development tools can improve engineering productivity without compromising solution quality.

Customer & Business Engagement

• Participate in customer workshops, requirement discussions, and product demonstrations.
• Assist in understanding customer challenges, processes, and desired business outcomes.
• Translate business problems into practical AI use cases and product enhancement ideas.
• Support the preparation of technical presentations, prototypes, and demonstration materials.
• Gather customer and stakeholder feedback to guide product improvement.
• Communicate technical concepts clearly to both technical and non-technical audiences.

Documentation & Knowledge Sharing

• Prepare and maintain:
  • Technical Documentation
  • Solution Notes
  • API Documentation
  • User Guides
  • Test Records
  • Deployment Instructions
  • Product Demonstration Materials
• Record development decisions, known limitations, and troubleshooting steps.
• Share technical findings, prototypes, and learning outcomes with the wider team.
• Contribute reusable code, templates, and technical knowledge to internal repositories.

Continuous Learning & Innovation

• Stay informed about developments in AI models, agent frameworks, Microsoft Azure, Microsoft Fabric, and modern software engineering.
• Participate in technical training, product discussions, hackathons, and knowledge-sharing activities.
• Explore new development methods that improve product quality, delivery speed, and user experience.
• Recommend practical ideas for new AI features, integrations, and product capabilities.

👤 Who You Are

• Passionate about building practical AI products rather than only experimenting with models.
• Strong in Python and comfortable applying software engineering fundamentals.
• Interested in LLMs, AI agents, RAG, data platforms, and intelligent applications.
• Capable of learning new technical concepts and applying them quickly.
• Able to break complex problems into manageable engineering tasks.
• Comfortable working independently while requesting guidance when necessary.
• Willing to engage with customers, consultants, developers, and business stakeholders.
• Able to explain technical ideas clearly and demonstrate working solutions.
• Detail-oriented when testing, debugging, and documenting software.
• Proactive, curious, and committed to continuous improvement.
• Product-minded and focused on creating solutions that deliver real user and business value.
• Responsible, collaborative, and growth-oriented, with the qualities of being humble, hungry, and smart.

🎓 Technical Skills & Qualifications

Education

Currently pursuing or recently completed a Diploma or Bachelor’s Degree in:

• Computer Science
• Software Engineering
• Artificial Intelligence
• Data Science
• Information Technology
• Information Systems
• Computer Engineering
• Or a related technical field

Candidates with strong practical project experience from other academic backgrounds may also be considered.

Programming & Software Engineering

• Strong proficiency in Python.
• Good understanding of:
  • Object-Oriented Programming
  • Data Structures
  • APIs
  • Application Logic
  • Error Handling
  • Debugging
  • Testing Practices
• Familiarity with Git-based version control.
• Ability to write readable, structured, and maintainable code.
• Experience building software applications, services, or automation solutions.

AI Application Development

• Hands-on experience through academic, personal, internship, hackathon, or open-source projects involving one or more of the following:
  • Large Language Models
  • AI Agents
  • Retrieval-Augmented Generation
  • Prompt Engineering
  • Machine Learning
  • Conversational AI
  • Intelligent Document Processing
• Understanding of how LLM-powered applications retrieve information, use tools, and generate responses.
• Awareness of AI limitations, testing requirements, and responsible AI considerations.

Cloud & Data Platforms

• Working knowledge or practical exposure to:
  • Microsoft Azure
  • Azure AI
  • Azure OpenAI
  • Microsoft Fabric
  • SQL
  • Data Pipelines
  • Semantic Models
  • Modern Analytics Architectures
• Basic understanding of structured and unstructured data.
• Familiarity with cloud-based application development is an added advantage.

RAG & Knowledge Technologies

• Basic knowledge or practical experience with:
  • Vector Databases
  • Embeddings
  • Semantic Search
  • Document Retrieval
  • Enterprise Knowledge Solutions
  • RAG Evaluation
• Ability to connect AI applications to data sources, documents, APIs, or databases.

Product Development & Delivery

• Demonstrated ability to build and complete working solutions.
• Evidence may include:
  • Personal Projects
  • Hackathon Projects
  • Open-Source Contributions
  • Startup Initiatives
  • Academic Capstone Projects
  • Deployed Applications
  • GitHub Repositories
• Strong problem-solving and product-thinking capabilities.
• Ability to consider user needs, business value, usability, and technical feasibility when developing solutions.

⭐ Added Advantage

• Experience developing front-end or back-end applications.
• Familiarity with JavaScript, TypeScript, React, Node.js, C#/.NET, FastAPI, Flask, or similar technologies.
• Experience using Azure AI services, Azure AI Search, Azure Functions, or Azure App Service.
• Exposure to Microsoft Fabric lakehouses, warehouses, notebooks, pipelines, or semantic models.
• Experience with agent orchestration or multi-agent workflows.
• Familiarity with model evaluation, guardrails, observability, or prompt testing.
• Experience using Docker, CI/CD pipelines, GitHub Actions, or Azure DevOps.
• Participation in technology competitions, AI challenges, hackathons, or startup projects.
• Experience presenting technical solutions to customers, lecturers, judges, or business stakeholders.
• A portfolio or GitHub profile demonstrating AI, data, software engineering, or product development work.

Certifications Are an Added Advantage

• Microsoft Certified: Azure AI Fundamentals
• Microsoft Certified: Azure Fundamentals
• Microsoft Certified: Fabric Analytics Engineer Associate
• Microsoft Certified: Azure AI Engineer Associate
• Other relevant AI, cloud, data, or software development certifications

📊 What Success Looks Like

Success in this internship will be demonstrated through:

• Delivery of functional AI prototypes and product features.
• Quality, readability, and maintainability of contributed code.
• Effective use of APIs, data sources, RAG, and AI models.
• Accuracy and completeness of testing and documentation.
• Ability to troubleshoot issues and apply technical feedback.
• Contribution to customer demonstrations and requirement discussions.
• Responsible use of AI-assisted development tools.
• Continuous learning and improvement in technical capability.
• Effective communication, collaboration, and ownership of assigned work.
• Ability to turn product ideas into practical, testable solutions.

🌱 Why Join SRKK Group?

• Build real AI applications, copilots, and intelligent agents.
• Gain hands-on experience with Azure AI, Azure OpenAI, Microsoft Fabric, LLMs, RAG, and agentic development tools.
• Work across the complete AI product lifecycle, from discovery and prototyping to testing, deployment, and improvement.
• Learn directly from engineers, consultants, architects, and customer-facing project teams.
• Gain exposure to real customer requirements and enterprise AI use cases.
• Strengthen your portfolio through practical product engineering experience.
• Access Microsoft-aligned learning resources, technical training, and certification opportunities.
• Participate in a collaborative environment that values experimentation, responsible innovation, and knowledge sharing.
• Build a career pathway toward roles such as:
  • AI Product Engineer
  • AI Engineer
  • Generative AI Engineer
  • AI Application Developer
  • Machine Learning Engineer
  • Data & AI Consultant
  • AI Solution Architect
• Potential opportunity for a full-time position based on business needs, internship performance, and available vacancies.

🚀 Join SRKK Group and turn bold AI ideas into practical products that solve real business challenges and create meaningful impact.