Director of AI

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About the Organization

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 agents—especially women—to 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.

Job Description

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 engineers—focused 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.

Job 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.

System and Infra Oversight:

• 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.

Team Building and People Management:

• 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.

Cross-functional Collaboration:

• 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.

Education Qualification/Required Skills & Experience

• 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.

For more information please check the Link

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