全职 AI-Native Software Developer 工作, 薪水, Thousands Of Years Media Federal Territory 公司招聘中 - Ricebowl

Build With AI. Build AI Into Products. Turn New Technology Into Working Software.

At Thousands of Years Media Sdn. Bhd. (ToYm), we are looking for an AI-Native Software Developer to build applications, features and internal systems where artificial intelligence is a fundamental part of how the product works.

You will support BiteShorts and other current or upcoming ToYm digital products, as well as new AI-driven tools and automation opportunities across the business.

This is not simply a role for someone who uses ChatGPT while coding.

We want a developer who understands how to use LLMs, AI APIs, agents, automation and modern AI development tools to build real production systems faster and create capabilities that were previously difficult or impossible to deliver.

Why This Opportunity Is Different

AI is changing both what software can do and how software is built.

At ToYm, you will work on both sides.

You will use AI-native development methods to increase development speed while also building AI directly into products and business workflows.

Projects may involve:

• AI-Powered Applications
• Intelligent Automation
• AI Agents
• Content Systems
• Recommendation or Personalisation
• Search & Discovery
• Internal Productivity Tools
• Customer Experiences
• Data Processing
• Media & Entertainment Applications
• New AI-First Products

We are looking for someone who experiments quickly but also knows how to turn successful experiments into reliable production systems.

What You Will Own

1. Build AI-Native Applications

• Design and develop applications where AI is a core capability.
• Integrate leading AI models and APIs into real products.
• Build user experiences that combine conventional software with AI-generated or AI-assisted outcomes.
• Turn prototypes into maintainable production applications.
• Continuously evaluate new AI capabilities that may create product or business value.

2. Build LLM-Powered Features

Develop features using technologies such as:

• Large Language Models
• Multimodal AI
• AI APIs
• Structured Outputs
• Function / Tool Calling
• Embeddings
• Retrieval-Augmented Generation (RAG)
• Semantic Search
• AI Agents
• Workflow Automation

Select appropriate approaches based on reliability, performance, cost and business requirements.

3. Build AI Agents & Automation

• Identify repetitive processes that can be automated.
• Build AI agents and automated workflows that perform useful business tasks.
• Connect AI systems with existing APIs, databases and business tools.
• Design human-review processes where full automation is inappropriate.
• Measure whether automation actually improves speed, quality or cost.

4. Develop Using AI-Native Workflows

Use modern AI development tools to accelerate:

• Coding
• Debugging
• Testing
• Refactoring
• Documentation
• Prototyping
• Research
• Code Review

You should understand how to use AI to increase engineering productivity without sacrificing code quality, security or maintainability.

5. Build Reliable AI Systems

AI output is probabilistic.

You will be expected to design systems that address:

• Hallucination
• Incorrect Outputs
• Prompt Injection
• Data Privacy
• Security
• Latency
• Cost
• Model Failure
• Output Validation
• Reliability

Implement appropriate guardrails, validation, fallbacks and monitoring.

6. Test & Evaluate AI Performance

• Define clear success criteria for AI features.
• Build evaluation datasets and testing processes where appropriate.
• Compare prompts, models and architectures.
• Measure accuracy, quality, latency and cost.
• Use evidence rather than assumptions when deciding which AI approach to deploy.

7. Build Complete Software Around AI

AI alone is not a product.

You should be able to build or contribute to:

• Frontend Interfaces
• Backend Services
• APIs
• Databases
• Authentication
• Cloud Deployment
• Integrations
• Monitoring

Create complete experiences where AI works reliably as part of a larger software system.

8. Explore New AI Opportunities

• Stay current with rapidly changing AI models, tools and development practices.
• Prototype promising new capabilities quickly.
• Evaluate whether new technology creates genuine user or business value.
• Recommend what ToYm should adopt, test or avoid.
• Help turn successful prototypes into scalable applications.

Who We Are Looking For

We care more about what you have actually built using AI than how many years you have worked or what certificates you hold.

Proven AI Development Work

You should be able to demonstrate AI-powered applications, automations, agents or systems that you personally built.

We want to understand:

• What did you build?
• What problem did it solve?
• Which AI models or tools did you use?
• Why did you choose that architecture?
• What did you personally develop?
• How did you test the output?
• How did you control errors or hallucinations?
• Was the system deployed and used?
• What measurable improvement did it create?

Working products and strong prototypes with clear thinking are more valuable than simply listing AI tools on your CV.

Strong Software Engineering Foundation

You should be able to write real software around AI systems.

Practical capability may include:

• Python
• JavaScript / TypeScript
• Backend Development
• APIs
• Databases
• Cloud Services
• Git
• Testing
• Deployment
• System Integration

You do not need to know every language or framework.

We need someone who can choose appropriate technologies and build reliable systems.

Strong AI Understanding

You should understand practical concepts such as:

• Prompt Engineering
• Context Management
• Structured Outputs
• Embeddings
• Vector Search
• RAG
• Tool Calling
• Agents
• Model Evaluation
• Token / API Cost
• Latency
• Guardrails
• AI Safety & Security

Experience with major AI model providers and development frameworks is valuable, but we care more about what you achieved with them.

What Matters More Than Years or Certificates

There is no strict minimum number of years and no strict degree requirement.

What matters is:

• What AI products have you built?
• Can you build beyond a simple API demo?
• Can you integrate AI into production software?
• Can you evaluate whether an AI system actually works?
• Can you manage accuracy, cost, latency and reliability?
• Can you use AI to accelerate your own development workflow?
• Can you rapidly learn as AI technology changes?
• Can you turn an idea into a working product?

Skills That Matter

• AI-Native Software Development
• LLM Integration
• AI APIs
• Prompt Engineering
• Retrieval-Augmented Generation (RAG)
• Embeddings & Vector Search
• AI Agents
• Tool / Function Calling
• Workflow Automation
• Model Evaluation
• Python
• JavaScript / TypeScript
• Backend Development
• APIs & Databases
• Cloud Deployment
• AI-Assisted Development
• Testing & Debugging
• Security & Guardrails
• Product Thinking

Our Values

• CUSTOMER-CENTRIC 
• PURPOSE-DRIVEN & RESULTS-ORIENTED 
• TEAMWORK 
• RESPONSIBILITY 
• EFFECTIVE EXECUTION 
• HUMBLE & LEARNING 
• PURSUIT OF EXCELLENCE 
• CONTINUOUS INNOVATION 
• CONTRIBUTE TO SOCIETY 

Rewards & Growth

• Build AI capabilities across ToYm’s digital products.
• Work on BiteShorts and other new applications.
• Experiment with rapidly emerging AI technologies.
• Develop AI-powered products and internal systems from an early stage.
• Work directly with Product, Technology and Management teams.
• Help shape ToYm’s future AI development capabilities.

This Role Is For You If…

You are already using AI to change how you build software.

You are interested not only in calling an AI API, but in creating reliable products, agents and systems around it.

You experiment quickly, measure what works and know when a prototype needs stronger engineering before reaching users.

You want to build products in an environment where AI is treated as a core technology capability, not an occasional feature.

Come build ToYm’s next generation of AI-powered products.

To Apply: Submit your resume, GitHub or technical portfolio where available, and examples of AI applications, agents, automations or systems you personally built. Explain the problem, your technical approach, your personal contribution and the result.