Junior AI Engineer

Deskripsi pekerjaan Junior AI Engineer Pt Cipta Piranti Sejahtera

ACCURATE INDONESIA

• is looking for a
• Junior AI Engineer

to help us ship Generative AI features that real users depend on. This is a hands-on implementation role, not a research role. You will spend most of your time building AI agents, wiring them into automated workflows, and turning prototypes into services that run reliably in production.

Qualifications

0–2 years of professional experience in software engineering, data engineering, automation, or AI/ML implementation. Strong fresh graduates with substantial hands-on Gen-AI projects are welcome to apply.

Bachelor's degree in Computer Science, Informatics, Information Systems, Engineering, Mathematics, or a related field — or equivalent demonstrable practical experience.

A portfolio of Gen-AI work you personally built — an agent, a RAG chatbot, an automation workflow, or an LLM-powered internal tool. GitHub repositories, deployed demos, or a walkthrough during interview all count. This matters more to us than years of experience.

• Technical Skills - Must Have
• Python
• solid working proficiency. You can build and structure a real application, not just run notebooks.
• LangChain
• practical experience building chains, agents, tools, retrievers, and memory. You understand what the abstractions do underneath, not only how to copy examples.
• n8n (or an equivalent workflow automation platform such as Make, Zapier, Dify, or Flowise)
• you have built multi-step workflows with branching, error handling, and external integrations. Direct n8n experience is a strong plus; if you come from another tool, we expect you to pick up n8n quickly.
• LLM API integration
• working with OpenAI, Anthropic, Google Gemini, or similar; understanding of tokens, context windows, temperature, function/tool calling, and structured output.
• Prompt engineering
• system prompts, few-shot examples, output schemas, and iterating on prompts based on observed failures.
• RAG fundamentals
• embeddings, chunking strategies, vector databases (Pinecone, Qdrant, Weaviate, Chroma, or pgvector), and similarity search.
• REST APIs and JSON
• you can read API documentation, authenticate, handle pagination, and debug a failing request.
• Git
• branching, pull requests, and collaborative workflow.
• SQL and basic database work
• querying, joins, and reading a schema you did not design.
• Ways of Working

Strong debugging instinct. When an agent gives a wrong answer, you can trace whether the problem is the prompt, the retrieval, the tool, or the data — and you do not stop at 'the model is bad'.

• Comfortable with ambiguity. Gen-AI requirements are rarely fully specified; you can propose a concrete approach and validate it fast.
• Ships and iterates. You would rather deliver a working v1 this week and improve it than perfect a design for a month.
• Reads documentation and release notes. This field changes monthly and we expect you to keep up without being told.

Clear written communication in Bahasa Indonesia and functional English — enough to read technical documentation, follow English-language sources, and write clear documentation.

• Aware of AI risk: data privacy, prompt injection, PII handling, and the limits of what an LLM output should be trusted to decide.
• Nice to Have
• Experience with LangGraph or other agent orchestration frameworks for stateful, multi-agent, or human-in-the-loop flows.
• Self-hosting and operating n8n (Docker, queue mode, environment variables, credential management).
• LLM observability and evaluation tooling — LangSmith, Langfuse, Ragas, or DeepEval.
• Backend API development with FastAPI, Flask, or Node.js/Express.
• Docker and basic CI/CD; deploying services to cloud (AWS, GCP, or Azure).
• Running open-weight models locally or self-hosted (Ollama, vLLM) and understanding the cost/quality tradeoff versus hosted APIs.
• Model Context Protocol (MCP), voice agents, OCR / document understanding, or multimodal use cases.
• Fine-tuning, LoRA, or embedding model adaptation.
• Frontend basics (React / Next.js / Streamlit) for building internal tools and demos.