The Agency Fund

AI Data Engineer

The Agency Fund

Non-profit Organizations · 2-10 employees

23 h ago
Remote data-engineer Mid (2-5 yrs) Full-time
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About the role

Design and build AI/ML evaluations and features for tech platforms, including LLMs and recommendation systems. Develop robust data pipelines and maintain production ML systems with a focus on scalability and reliability.

What they look for

Python PyTorch TensorFlow HuggingFace LLM RAG Machine Learning Data Pipelines NLP Recommendation Systems AWS GCP Azure Cloud Infrastructure Model Inference Prototyping

Requirements

Requires 3-7 years of software engineering experience with at least 2 years focused on AI/ML systems. Proficiency in Python and experience with AI frameworks and cloud infrastructure is essential.

Benefits

Fully remote Flexible working environment

Full description

About The Agency Fund

The Agency Fund (TAF) is a US non-profit funder-doer that builds projects to expand human agency at scale. We embed engineers and product managers directly inside evidence-based nonprofits across East Africa, South Asia, and beyond — helping them build data infrastructure, run experiments, and scale impact through automation and product thinking. Our small, global team combines expertise in software, AI, social psychology, and development economics, and our community of 200+ partner organizations reaches millions of people annually.

We're an entrepreneurial team that operates with minimal hierarchy — everyone contributes to a shared mission in unique ways.

The Role

We're looking for an AI/ML Engineer to join our team. You'll design, build, and deploy AI/ML data systems that power Agency Fund's platforms and partner applications — from large language model integrations and recommendation engines to data pipelines and evaluation frameworks. Your work will directly improve outcomes for millions of people served by our NGO partners.

What You'll Do

  • Design and build AI/ML evaluations and features for Agency Fund's tech platforms and partners (LLMs, NLP, recommendation systems, etc.)
  • Develop robust data pipelines and evaluation frameworks for model training and inference and post-deployment efficacy
  • Work closely with behavioral scientists and researchers to translate insights into AI-powered features
  • Architect and maintain production ML systems with an emphasis on observability, performance, reliability and scalability
  • Conduct rapid prototyping and experimentation to validate AI approaches before full buildout
  • Document technical decisions and maintain engineering standards across AI components
  • Stay current with applied AI research and bring relevant advances to the team

Who You Are

You might be a great fit if you:

  • Have 3–7 years of software engineering experience with at least 2 years focused on AI/ML systems
  • Are proficient in Python and have hands-on experience with AI/ML frameworks (PyTorch, TensorFlow, HuggingFace, etc.)
  • Have built and deployed LLM-powered applications or retrieval-augmented generation (RAG) systems
  • Understand ML fundamentals: model training, evaluation, fine-tuning, and inference optimization
  • Are comfortable with cloud infrastructure (AWS, GCP, or Azure) and have deployed models in production
  • Communicate technical concepts clearly to non-engineering audiences
  • Care deeply about building AI responsibly and with direct social benefit

Bonus points if you have:

  • Experience with multilingual NLP or working with low-resource languages
  • Familiarity with behavioral science or designing AI for behavior change
  • Prior work in global health, international development, or social impact technology
  • Experience with data annotation pipelines and evaluation methodology for LLMs
  • Background in AI safety, alignment, or responsible AI frameworks

Why Join Us

  • Work with a kind, talented, and mission-driven team
  • Collaborate with bold thinkers across social impact, data, and product innovation
  • Shape projects that directly expand human agency
  • Fully remote and flexible working environment
  • Competitive compensation commensurate with experience

Location

Remote (Sub-Saharan African or South Asia)

  • Flexible time zone

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