Key Responsibilities

Technical Vision and Architecture
:
Define and implement a robust and scalable AI architecture tailored for agricultural applications. This includes designing hybrid edge\cloud infrastructures
,
optimizing machine learning model deployment frameworks, and ensuring system compatibility for field\-level deployment in rural and resource\-constrained environments.

AI Leadership and Supervision :
Lead and mentor cross\-functional teams of AI\/ML researchers and engineers in the development of predictive models for precision agriculture , disease and pest forecasting , crop yield prediction , and climate\-resilient farming. Ensure all RD efforts are aligned with real\-world challenges and validated through field data and trials.

Collaborative RD and Ecosystem Engagement :
Establish and manage strategic collaborations with premier research institutions, agri\-startups, and ecosystem enablers to co\-develop, pilot, and scale innovative AI solutions. Drive translational research by facilitating joint studies, data\-sharing protocols, and technical exchanges.

Integration with IoT and Smart Platforms :
Guide the integration of AI models with IoT\-based sensor networks , drone imagery, and farm\-level data platforms to enable holistic and real\-time farm intelligence systems. This includes developing APIs, sensor\-data pipelines, and analytics dashboards for actionable insights.

Responsible and Ethical AI :
Ensure the implementation of responsible AI practices, including model fairness , bias mitigation , data transparency, and compliance with data privacy standards (both domestic and international). Foster trust and accountability in AI applications impacting rural communities and livelihoods.

Technical Representation and Advocacy :
Represent ANNAM.AI in key technical forums including national grant review panels, policy think tanks, global research consortia, and international conferences. Advocate for science\-driven, inclusive, and scalable AI policies for agriculture and rural development.
Candidate Profile
Educational Qualifications and Skills

M.Tech\/MS\/PhD (preferred) in Computer Science, Data Science, AI, or related fields.

Minimum 7+ years of experience in AI\/ML system design, with at least 2 years in a leadership role.

Proficiency in frameworks like TensorFlow, PyTorch, Keras; expertise in model training, data pipelines, and AI deployment.

Experience with agri\-tech, remote sensing, or satellite data is desirable.

Strong strategic thinking and problem\-solving skills.

Excellent communication and cross\-functional collaboration abilities.

Performance\-Based Incentives: Based on board approval,. linked to KPIs such as fund mobilization, compliance, audit timeliness, digital efficiency, and startup investment governance.
Separation Clause: One monthotice in year one, two months in subsequent years or salary in lieu.

Chief Technology Officer

Job Description

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