Junior Agronomist - AI and Data Quality (India)

Location

Surat, Gujarat – Remote option for exceptional candidates

About KissanAI

KissanAI is a fast‑growing agri‑tech startup building large‑scale language models and data products tailored to the agricultural sector. Our team blends agronomy, data science, and artificial intelligence to deliver decision‑support tools that help farmers, ag‑input companies, and researchers drive sustainable productivity.

Why this role matters

High‑quality agronomic data is the backbone of any credible AI solution in agriculture. As a Junior Agronomist, you will curate and validate the datasets that power our cutting‑edge language models, ensuring farmers and scientists alike can trust our recommendations.

Key responsibilities

• Collaborate with domain scientists, data engineers, and machine‑learning experts to define data requirements for new product features.
• Collect, clean, annotate, and QC diverse agronomic datasets (crop management, soil, weather, pest and disease, satellite imagery, extension literature).
• Contribute agronomic expertise during model‑development sprints: advise on feature selection, label definitions, and error analysis.
• Document data curation processes, creating playbooks and quality metrics that can be reproduced at scale.
• Communicate findings, gaps, and improvement ideas clearly to both technical and non‑technical stakeholders.
• Stay current on agronomy research, government advisories, and AI applications in agriculture to identify valuable new data sources.

What we are looking for

Must‑haves

• Bachelor’s or Master’s degree in Agronomy, Crop Science, Soil Science, Agricultural Engineering, or a related discipline from a reputed agricultural university or institute.
• Strong written and spoken English; able to write crisp documentation and present to multidisciplinary teams.
• Genuine curiosity about artificial intelligence and enthusiasm for solving open‑ended problems.
• Detail‑oriented mindset with a passion for data quality and reproducibility.

Nice‑to‑haves

• Hands‑on coursework or projects involving AI, data analytics, or remote sensing.
• Working knowledge of Python for basic data wrangling or exploratory analysis.
• Proficiency in one or more Indian languages (Hindi, Marathi, Tamil, Telugu, Kannada, Gujarati, etc.) for interpreting regional agronomic content.
• Field experience with crop trials, soil sampling, or extension services.

What you will gain

• Mentorship from seasoned agronomists, data scientists, and AI researchers.
• Exposure to large language model workflows, from prompt engineering to evaluation.
• Ownership of data pipelines that directly influence farmer‑facing products.
• A culture of experimentation, continuous learning, and impact on Indian agriculture at scale.

Compensation and benefits

• Competitive salary package commensurate with experience.
• Flexible work options: on‑site in Surat with occasional field visits, or remote for candidates who have demonstrated excellence.
• Fast career progression in a rapidly growing startup.