Job description for IT & Technology Team at PT Agrinas Pangan Nusantara (Persero)
PT Agrinas Pangan Nusantara (Persero) is a state-owned enterprise that has transformed from PT Yodya Karya (Persero). The company operates through three main strategic pillars: Food, Engineering Consultancy, and Construction. Committed to strengthening Indonesia's food sovereignty, Agrinas Pangan Nusantara builds an integrated ecosystem spanning production, distribution, and infrastructure development. We believe that a thriving agricultural sector is the foundation of an independent and prosperous nation. We are currently looking for competent and passionate individuals to join our IT & Technology team in East Jakarta, DKI Jakarta, Indonesia.
We are currently hiring for the following IT positions:
- IT Support
- Data Engineer
- AI Engineer
- QA Engineer
- IT Support
Requirement:
- Minimum Vocational High School (SMK) in Information Technology, Computer Engineering, Computer Science, or a related field.
- Fresh graduates are welcome; experience in IT Support or Infrastructure Support is an advantage.
- Good understanding of IT infrastructure and networking fundamentals.
- Strong troubleshooting and analytical skills.
- Ability to work independently and collaboratively.
Technical Skill:
- Networking: TCP/IP, DNS, DHCP, basic subnetting, LAN/WAN/Wi-Fi troubleshooting, router & switch configuration (MikroTik/Cisco), VPN, and basic firewall.
- Infrastructure & Server: Linux Server (Ubuntu/CentOS), Windows Server & Active Directory, VMware/Proxmox, and storage & backup fundamentals.
- System Operations: System monitoring, incident handling & troubleshooting, software installation & configuration, and user & access management.
2. Data Engineer
Requirement:
- Minimum 3–5 years of experience as a Data Engineer.
- Strong analytical thinking and problem-solving skills.
- Able to work collaboratively in a fast-paced environment.
Technical Skill:
- Minimum 3–5 years of experience as a Data Engineer.
- Strong analytical thinking and problem-solving skills.
- Able to work collaboratively in a fast-paced environment.
3. AI Engineer
Requirement:
- Minimum 3–5 years of experience in AI/ML Engineering
- Hands-on experience in LLM fine-tuning and model optimization in production
- Familiar with Generative Engine Optimization (GEO) strategies and implementation
- Strong understanding of how AI search engines and LLMs retrieve and surface information
- Able to work across technical teams and content/strategy stakeholders
Technical Skill:
- LLM Fine-Tuning (LoRA, QLoRA, PEFT — domain adaptation for specific industries)
- Model Serving & Inference Optimization (vLLM, Ollama, TGI, or similar)
- Generative Engine Optimization — structuring and publishing content to improve AI search visibility (Perplexity, ChatGPT, Gemini)
- Familiar with structured data markup, semantic content strategy, and citation optimization for LLM indexing
- Hugging Face ecosystem (Transformers, Datasets, PEFT, Trainer API)
- Python — model training pipeline, data preparation, evaluation
- GPU compute management (CUDA basics, cloud GPU — RunPod, Lambda, GCP/AWS)
- LLM Evaluation (perplexity, BLEU, ROUGE, domain-specific benchmarking)
4. QA Engineer
Requirement:
- Minimum 3-5 years of experience in software quality assurance, covering both manual and automated testing
- Proven experience designing and executing integration testing and load/performance testing on production-grade systems
- Experience testing web, mobile, and API-based applications with multiple connected systems
- Strong analytical skills and attention to detail, with the ability to write clear bug reports and test documentation
- Able to work collaboratively with developers, product owners, and business users
Technical Skill:
- Manual Testing (test plan and test case design, exploratory, regression, and UAT support)
- Test Automation for Web/UI (Playwright, Cypress, Selenium, or similar)
- API Testing and Automation (Postman, REST Assured, or similar)
- Integration Testing across multi-system flows (e.g., POS, ERP, WMS, third-party APIs)
- Load and Performance Testing (k6, JMeter, Locust, Gatling, or similar), including bottleneck analysis and reading key metrics (response time, throughput, error rate, p95/p99)
- SQL for data validation and test data preparation
- CI/CD integration for automated test suites (GitHub Actions, GitLab CI, Jenkins, or similar)
- Defect and test management tools (Jira, TestRail, or similar)
- Git, plus basic Linux and Docker for test environment setup
