Jobs at Wadhwani AI

Own pedagogical and assessment integrity for AI-based foundational literacy and numeracy tools across multiple countries. Design learning and assessment logic, validate AI-scored outputs, adapt content to languages and curricula, manage field data collection and multi-country rollout, maintain implementation trackers, and engage governments, partners, and funders. Develop M&E frameworks, reporting inputs, proposals, and policy-ready insights while ensuring pedagogical validity, data quality, and assessment reliability.

Own growth strategy, market expansion, deal, proposal, and go-to-market workstreams. Build market sizing models, prioritization frameworks, partnership structures, pricing logic, and investment cases. Support senior leaders in discussions with governments and multilaterals, track opportunities, and coordinate across product, technology, marketing, policy, and delivery teams. Guide junior team members and improve internal tools and processes.

Owns data collection and annotation operations, defines product specifications and user flows, and supports apps and internal tools through delivery. Manages field teams, implementation partners, pilots, feedback loops, product metrics, and deployment improvements. The role also contributes to grant and partnership work while collaborating with engineering and ML teams. Candidates need product or delivery experience, technical fluency, data comfort, field deployment exposure, and familiarity with AI or ML products and data protection.

Own fundraising workstreams including donor research, opportunity pipeline tracking, proposal and pitch-deck development, donor engagement support, funding-model analysis, and maintenance of donor systems. Coordinate across growth, operations, product, finance, and program teams while supporting thought leadership and WAIG’s global positioning as an AI-for-public-good partner.

Build and deploy mobile applications for low-connectivity environments, backend services on AWS, internal data-review tools, and APIs or on-device integrations for machine-learning models. Own releases, monitoring, logging, security, testing, CI, documentation, and rapid prototypes. The role requires production application ownership, database design, mobile release experience, offline-first development, asynchronous collaboration, and occasional field deployment travel.