AI Engineer (5 Positions)
- Career Category: Computer - Programming, Computer - General, Engineering
- Schedule:Full-time
- Salary: Negotiable
Department: AI Development
Reports To: Senior Operations Manager
Working Hours: 8:00am to 5:00pm (Monday to Friday and Half Saturday once or twice a month)
In this role, you will build, optimize, and deploy scalable AI capabilities—including Large Language Models (LLMs), computer vision systems, or generative AI applications—into our core product architecture. You will collaborate closely with Data Scientists to transition prototypes into robust, low-latency microservices.
- Model Deployment & Integration: Seamlessly integrate machine learning models into production software environments, utilizing containerization (Docker, Kubernetes) and microservice architectures (FastAPI, Flask).
- LLM Ops & Engineering: Design, implement, and optimize retrieval-augmented generation (RAG) pipelines, fine-tune open-source models, and manage prompt engineering architectures.
- Pipeline Automation: Build and maintain automated machine learning pipelines (MLOps) for continuous integration, continuous deployment, and automated retraining of production models.
- Performance Optimization: Quantize, cache, and optimize models for high throughput and ultra-low latency, minimizing compute costs and resource footprints.
- Monitoring & Maintenance: Implement data drift detection, model performance tracking, and robust logging structures to ensure system reliability post-deployment.
- Bachelor's Degree in Computer Science, Software Engineering, or a heavily technical discipline (or equivalent practical experience)
- Working explicitly as a Software Engineer or DevOps Engineer in a production-tier AI environment for 1 year
- Languages: Advanced proficiency in Python (with libraries like PyTorch, TensorFlow, Hugging Face, or LangChain) and familiarity with backend languages (Node.js, Python, or Java).
- MLOps & DevOps: Proven experience with Docker, CI/CD tools, and orchestrators like Apache Airflow, Prefect, or Kubeflow.
- Cloud Infrastructure: Deep familiarity with cloud environments (AWS, OpenStack, GCP, or Azure) and infrastructure as code (Terraform).
- Databases: Solid understanding of vector databases (Pinecone, Milvus, Chroma, or Qdrant) alongside relational (MariaDB, PostgreSQL) and non-relational storage systems.
- Strong architectural thinking: The ability to evaluate the compute cost, latency trade-offs, and scalability of different AI models before putting them into production.
DevOps (5 Positions)
- Career Category: Computer - General, Computer - Programming
- Schedule:Full-time
- Salary: Negotiable
Department: AI Development
Reports To: Senior Operations Manager
The DevOps Engineer will be responsible for bridging the gap between software development and IT operations, enabling faster and more reliable delivery of applications and services. This role involves managing both on-premises and cloud infrastructure, automating deployment pipelines, ensuring system reliability, and implementing robust monitoring and security practices. The ideal candidate will work closely with developers, system administrators, and network engineers to streamline workflows, improve efficiency, and maintain high system availability.
Working Hours: 8:00am to 5:00pm (Monday to Friday and Half Saturday once or twice a month)
- Design, implement, and maintain CI/CD pipelines for automated build, test, and deployment processes.
- Manage containerized environments (Docker, Kubernetes) including scaling, upgrades, and troubleshooting.
- Monitor system performance, availability, and security using tools like Prometheus, Grafana, OpenSearch, etc.
- Collaborate with developers to ensure smooth deployment and integration of applications.
- Implement automated backup, recovery, and failover processes.
- Maintain security best practices for servers, cloud accounts, and CI/CD workflows.
- Troubleshoot production issues and coordinate with relevant teams to resolve them quickly
- Bachelor's Degree in Computer Science, Information Technology, or related field (or equivalent work experience).
- Working explicitly as a DevOps Engineer for 1 year
- Proven experience as a DevOps Engineer or in a similar role.
- Strong knowledge of Linux/Unix systems administration.
- Hands-on experience with CI/CD tools (Jenkins, GitLab CI, GitHub Actions, etc.).
- Experience with containerization and orchestration (Docker, Kubernetes).
- Proficiency in scripting languages (Bash, Python, etc.).
- Knowledge of version control systems (Git).
- Experience with monitoring, logging, and alerting systems.
- Good understanding of networking, security, and load balancing concepts.
- Strong architectural thinking: The ability to evaluate the compute cost, latency trade-offs, and scalability of different AI models before putting them into production.
Data Engineer (5 Positions)
- Career Category: Computer - Programming, Computer - General, Engineering, Computer - Networking
- Schedule:Full-time
- Salary: Negotiable
Department: AI Development
Reports To: Senior Operations Manager
Location: Educational Broadcasting Cambodia, EBC, Phnom Penh
Working Hours: 8:00am to 5:00pm (Monday to Friday and Half Saturday once or twice a month)
In this role, you will design, implement, and optimize the automated pipelines (ELT/ETL) that pull raw data from diverse sources—including relational databases, third-party APIs, and production event streams—and transform it into clean, high-performance, analytical datasets.
You will be the architect of our data reliability. You will work closely with Data Scientists, AI Engineers, and Business Analysts to understand their data requirements, ensure strict data quality, optimize storage structures, and maintain low-latency query performance across our data warehouse and Lakehouse platforms.
- Pipeline Development & Integration: Design, write, and maintain robust, idempotent data pipelines to ingest structured and unstructured data from transactional systems, SaaS applications, and internal microservices.
- Data Transformation & Modeling: Build and document scalable transformation layers (using SQL, Python, or dbt). Design efficient, clean analytics schemas (e.g., Star Schema, dimensional models, or unified lakehouse layers) tailored for downstream consumption.
- Workflow Orchestration: Author, schedule, and monitor automated workflow DAGs (Directed Acyclic Graphs) using modern orchestrators. Implement proactive error handling, graceful retry logic, and fallback mechanisms for pipeline failures.
- Data Quality & Observability: Implement automated data validation frameworks, schema enforcement rules, and alerting systems to flag anomalies or data drift before they reach downstream reporting layers.
- Performance & Cost Optimization: Continually audit database performance. Implement optimal data partitioning, indexing, file compaction, and pruning strategies to optimize query execution speeds while controlling cloud compute and storage costs.
- Bachelor's Degree in Computer Science, Software Engineering, Information Systems, or a heavily technical quantitative discipline (or equivalent practical experience)
- Operating explicitly as a Data Engineer building production-grade infrastructure, rather than just configuring lightweight ingestion tooling for 1 year
- Languages: Advanced, expert-level proficiency in SQL (complex analytical queries, window functions, and query plan troubleshooting) and strong fluency in Python or R for scripting and pipeline automation.
- Data Warehousing & Lakehouses: Deep hands-on experience with at least one enterprise cloud data platform (e.g., Snowflake, BigQuery, Databricks, or Redshift).
- Orchestration & Tooling: Production experience using data workflow orchestrators (such as Apache Airflow, Prefect, or Dagster) and transformation tools like dbt.
- Data Formats & Architecture: Strong familiarity with handling high-velocity data and working with specialized analytical file formats (e.g., Parquet, JSONL, Avro) alongside traditional relational database engines (e.g., MariaDB, PostgreSQL).
- A strong "defense-in-depth" engineering mindset: You build pipelines under the assumption that upstream schemas will change, APIs will time out, and incoming data will occasionally be corrupted.
- Excellent cross-functional communication: The ability to collaborate with non-technical business units to define clean definitions for metrics, while translating those definitions into strict, technical pipeline logic.
Front-End Developer (5 Positions)
- Career Category: Computer - Programming, Computer - General
- Schedule:Full-time
- Salary: Negotiable
Department : AI Department
Reports To : Head of AI Department
Location : Educational Broadcasting Cambodia, EBC, Phnom Penh
In this role, you will build responsive, accessible, and high-performing user interfaces for our web applications. You will work closely with back-end developers, designers, and product managers to translate designs and requirements into clean, maintainable code that delivers a great user experience.
- UI Development: Build responsive, cross-browser user interfaces using modern JavaScript frameworks such as React, Vue, or Angular.
- Design Implementation: Translate wireframes, mockups, and design systems into pixel-accurate, reusable components.
- API Integration: Consume RESTful and/or GraphQL APIs, and manage application state and data flow between front-end and back-end services.
- Performance Optimization: Optimize page load times, bundle sizes, and rendering performance, and follow best practices for web accessibility (WCAG).
- Testing & Quality: Write unit and end-to-end tests, participate in code reviews, and help maintain a consistent component library.
- Collaboration: Work closely with UI/UX designers and back-end engineers to ensure a seamless, cohesive product experience across devices.
- Bachelor's Degree in Computer Science, Software Engineering, or a related technical discipline (or equivalent practical experience).
- Front-end Developer or Software Engineer building production-grade web applications for 2 years
- Languages: Strong proficiency in HTML, CSS, and modern JavaScript/TypeScript, with a solid understanding of responsive and mobile-first design.
- Frameworks: Hands-on experience with front-end frameworks and libraries such as React, Vue.js, Angular, or Next.js.
- Styling & Tooling: Familiarity with CSS preprocessors or utility frameworks (Sass, Tailwind CSS) and build tools such as Webpack or Vite.
- Version Control & Testing: Working knowledge of Git, and experience with testing frameworks such as Jest, React Testing Library, or Cypress.
- Strong eye for detail and a good sense of UI/UX best practices, usability, and visual consistency.
- Good communication skills and the ability to collaborate effectively with designers and cross-functional teams.
