Skill diminta
CommunicationDecision MakingJavaNode.jsPython
Deskripsi
Job Requirements
What are we looking for
- 5+ years of backend engineering experience (Java / Spring preferred; strong Python or Node.js engineers are welcome)
- Hands-on experience building LLM powered applications using OpenAI, Anthropic, MCP tool orchestration, etc
- Strong prompt engineering skills, especially for structured outputs (JSON schemas, function calling, tool use)
- Experience with event-driven architectures: webhooks, message queues, async/background processing
Comfortable operating in early-stage environments- ambiguity, speed, and ownership are part of the job (We currently support 1,800 farmers and are building toward 10M.
- Good to know
- Yes, you will go out into the field and get your feet dirty with some rice farming
Everyone is generally remote so you need to be able to communicate really well and use many types of communication mediums including chat, call, video, etc.
- Experience in AgTech or field-operations / on-ground workforce software
- Exposure to geospatial data (GPS, mapping, routing or optimisation problems)
- Experience building multilingual LLM applications, especially Indonesian and/or Vietnamese
- What You will Own
- Design and build the Agent Control Plane (execution framework, decision logging, override system)
- Implement agents with LLM-based decision making
- Create APIs for Territory Managers to review/approve agent proposals
- Work directly with product lead on prompt engineering
- How to Apply (and be seen)
- AI Portfolio (REQUIRED)
- You MUST demonstrate hands‑on AI experience through a portfolio showing your projects (Github Links)
- Programming Languages: Java
- with the
- Spring
- framework is preferred, but the team is also open to strong engineers in
- Python
- or
- Node.js
AI/LLM Application Building
- Hands-on experience developing applications powered by LLMs such as
- OpenAI
- Anthropic
- , or similar APIs.
Prompt Engineering
- Strong skills in creating prompts, specifically for structured outputs like
- JSON schemas
- function calling
- , and
- tool use
Architectural Knowledge
- Experience with
- event-driven architectures
- , including webhooks, message queues, and asynchronous or background processing.
Operating Mindset
Comfort working in early-stage, fast-paced environments characterized by ambiguity and high ownership