Backend Engineer (AI Agent)

About Rize

Rize (rize.farm) is a leading Agri-Tech startup uniquely positioned to build solutions that make rice cultivation more sustainable and improve farmer livelihoods in Asia. These sustainable solutions are urgently needed as rice cultivation is one of the largest polluting forms of agriculture globally. Formed through a joint venture between Temasek, Wavemaker Impact, Breakthrough Energy Ventures, and GenZero, Rize's technology captures vital agricultural data essential for implementing sustainable farming practices. This makes rice farmers more climate-resilient, increases their crop yields, lowers costs, and facilitates efficient access to finance. Rize currently has operations in Indonesia and Vietnam and plans to expand further within the region. To expand, Rize is unlocking climate/green financing facilities to help serve more farmers in their transition to sustainable rice cultivation. Rize has recently received substantial global media attention, acknowledging our efforts in this journey. Please read more here: Bloomberg, Business Insider, DealStreetAsia.

What are we building

We are developing a platform which will help our field operations team to effectively manage their task, capture cultivation logs from million plus hectares of paddy fields, effectively manage the supply chain of agri-inputs and aggregate third party services required during the lifecycle of paddy fields. The Current tech stack includes React Native for mobile applications, ReactJs for web app powered by Rest APIs developed with JAVA using Spring and Hibernate.

What you'll build: You'll create the first autonomous agent for our workforce management platform - a scheduling agent that helps 50+ field agronomists coordinate sustainable rice farming operations across 7,000 hectares in Indonesia and Vietnam.

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, or similar APIs

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:

Experience in AgTech or field-operations / on-ground workforce software

Exposure to geospatial data (GPS, mapping, routing or optimization problems)

Experience building multilingual LLM applications, especially Indonesian and/or Vietnamese

What you'll 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