Job Description

We are seeking a Data Developer who is passionate about data systems, backend development, and AI-driven solutions. In this role, you will contribute to designing, building, and maintaining data-driven backend solutions that power our analytics, applications, and intelligent AI agents. Working closely with senior developers and data engineers, you will help develop and optimize data pipelines, APIs, databases, and AI agent workflows that ensure data reliability, scalability, and intelligent automation across our organization.

This position is ideal for recent graduates or early-career professionals who are eager to grow their technical skills and gain hands-on experience in backend development, data engineering, and AI agent development , especially within the exciting world of gaming and data technology.

Job Requirements

Backend & Data Pipeline Development

• Assist in designing and developing scalable backend services and real-time/ batch data pipelines for data collection, processing, and analysis, with a focus on Flink-based real-time data processing.
• Support the creation of RESTful APIs or microservices that enable smooth data integration between systems, AI agent components, and real-time data streams.
• Contribute to the development of backend components using Python, Java (for Flink development), and where applicable, Golang (Go).
• Help implement and maintain ETL (Extract, Transform, Load) processes, as well as real-time ELT/ streaming data ingestion using Apache Flink, Flink SQL, Kafka, and Redis.
• Write clean, efficient, and well-documented code following best software development practices, including Flink job development and SQL optimization for real-time pipelines.
• Assist in designing and maintaining real-time data pipelines with Apache Flink: develop Flink jobs (Java) and write Flink SQL for real-time data transformation, aggregation, and delivery.
• Understand fundamental principles of Apache Kafka (message queuing, topic management, stream processing) and Redis (in-memory data storage, caching, data structures) to support real-time data pipeline development and optimization.

AI Agent Development

• Assist in designing and building AI agents and multi-agent workflows that automate complex data and business processes.
• Contribute to integrating Large Language Models (LLMs) into backend systems using frameworks such as LangChain, LlamaIndex, or similar agentic libraries.
• Help develop tool-use and function-calling capabilities that enable AI agents to interact with internal APIs, databases, and external services.
• Support the implementation of memory, context management, and retrieval-augmented generation (RAG) pipelines to enhance agent performance.
• Assist in evaluating, monitoring, and iterating on AI agent behaviour, accuracy, and reliability in production environments.

Database & Data Management

• Work with SQL and NoSQL databases (e.g., PostgreSQL, MongoDB) to design and maintain structured data storage, including those supporting AI agent state and memory.
• Support database optimization tasks, including query tuning and performance monitoring.
• Contribute to maintaining data warehouses used for reporting, analytics, and AI model grounding.

Automation & Monitoring

• Assist in automating data processing tasks, backend workflows, and AI agent orchestration to improve efficiency.
• Monitor backend system performance and help resolve issues in data pipelines (both batch and real-time), integrations, and agent execution flows.

Collaboration & Learning

• Collaborate with data engineers, ML engineers, analysts, and software developers on cross-functional projects involving both data and AI systems.
• Participate in code reviews, design discussions, and technical documentation.
• Continuously learn new tools, frameworks, and technologies across backend, data (including real-time processing) and AI agent development.

Qualifications

• Bachelor's degree in Computer Science, Software Engineering, Data Engineering, or a related field.
• Basic knowledge of Python and SQL. Familiarity with backend frameworks (e.g., FastAPI, Django, or Flask) is a plus.
• Experience or interest in Golang (Go) development is a strong advantage.
• Understanding of fundamental principles of Apache Kafka (streaming data) and Redis (in-memory caching/storage) is required.
• Exposure to AI/LLM frameworks (e.g., LangChain, LlamaIndex, OpenAI API, or Anthropic API) or an enthusiasm to learn is highly desirable.
• Understanding of data pipelines, ETL/ELT concepts, and database systems (with emphasis on real-time data processing).
• Familiarity with agentic concepts such as RAG, tool use, prompt engineering, or multi-agent orchestration is a bonus.
• Exposure to cloud platforms (AWS, GCP, or Azure) or container tools (Docker, Kubernetes) is advantageous but not required.
• Strong analytical thinking, attention to detail, and a passion for learning.
• Ability to work collaboratively in a team environment and adapt to new challenges.
• Enthusiasm for backend, data (including real-time processing), and AI development, with an interest in applying these skills to real-world projects and gaming technologies.

Skills