Director Of AI

Job Title: Director of AI

Location: Bangalore

Experience Level: 12+ years

Reports To: CTO

About Digital Green:

Digital Green is a global development organization enhancing the cost-effectiveness of public extension systems through an AI-powered assistant designed for frontline extension workers. By partnering with governments, we strengthen agricultural extension services with innovative AI-driven solutions embedded within local communities. Our technology empowers extension agentsespecially womento deliver personalized advisories in local languages, helping farmers improve productivity, incomes, and climate resilience at a fraction of the cost of traditional approaches.

Our cutting-edge AI solutions enhance decision support, provide real-time insights, and drive more efficient, data-driven agricultural practices. Farmer.Chat, our AI-driven digital assistant, offers localized and scalable support, enabling smallholder farmers to adopt sustainable practices and access market opportunities with ease. Through strategic collaborations with OpenAI, Meta, and Google, we are advancing responsible AI governance, ensuring inclusive and equitable AI applications in digital agriculture to empower farming communities worldwide.

About the Role:

We are seeking a visionary and technically astute Director of AI to lead and scale our AI initiatives, with a primary focus on LLM lifecycle management, deployment infrastructure, fine-tuning workflows, and real-world agent integration. You will lead a cross-functional team comprising MLOps, ML Infrastructure, LLM Evaluation, and Applied ML engineersfocused on building domain-specific, production-grade generative AI systems.

This role is ideal for a hands-on leader who brings deep expertise in AI, thrives in ambiguity, loves building and mentoring teams, and can collaborate across research, engineering, and product.

Key Responsibilities:

Technical Leadership:

• Help define and drive the AI vision and roadmap for the company with a focus on Large Language Models, synthetic data, and intelligent agents
• Oversee the end-to-end lifecycle of LLM systems: pretraining, fine-tuning, evaluation, alignment, and deployment
• Guide architectural decisions around retrieval-augmented generation (RAG), prompt orchestration, agent-based reasoning, and reinforce fine tuning
• Stay ahead of cutting-edge techniques such as LoRA, PEFT, RLHF, quantization, pruning, and actively lead experimentation and adoption across teams

• Provide oversight on cloud-native infrastructure (Kubernetes, Terraform, Vertex AI, Sagemaker, etc.), CI/CD pipelines, and model-serving systems (Triton, TorchServe)
• Drive efficiency and scalability through observability, hallucination tracking, token usage management, and compliance enforcement

• Build and grow a high-performing team of applied ML engineers, MLOps engineers, evaluators, and applied scientists
• Mentor senior engineers and lead career development, performance reviews, and team health initiatives
• Promote an inclusive, curious, and collaborative culture that encourages innovation, experimentation, and ownership

• Work closely with product, design, and engineering teams to convert ambiguous business needs into robust AI applications
• Represent the AI team in leadership forums, aligning technical roadmaps with strategic goals
• Evangelize LLM capabilities, risks, and opportunities across the organization to facilitate adoption

• Deep experience (10+ years) in machine learning, NLP, or deep learning, with hands-on exposure to fine-tuning and deployment
• Proven success building and scaling AI platforms or products in production (generative AI or LLMs is an extra plus)
• Expertise in tools like HuggingFace Transformers, LangChain, MLflow, and Kubeflow
• Experience managing and mentoring senior ML engineers and MLOps teams
• Strong understanding of data pipelines, embedding systems, vector databases, and multi-modal architectures
• Excellent communication skills with a knack for translating complex AI topics to diverse audiences

• Publications, Patents and/or open-source contributions in AI fields
• Experience building or evaluating LLM-based agents
• Exposure to domain-specific AI applications that have been put in production
• Learning attitude and agile approach to development.
• Strong motivation for using technical skill to build something for good

• Opportunity to shape the future of our AI strategy from the ground up
• Competitive salary and flexible work environment
• Budget for conferences, research exploration, and tooling

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