Senior AI Engineer (*3-Year LTE)

About the role

The Foundation is a nonprofit dedicated to fighting poverty, disease, and inequity globally. We are committed to reflecting the diversity of our global population in our workforce and providing exceptional benefits.

Responsibilities

• Design and build agentic AI systems — multi-step workflows, tool use, and autonomous task orchestration using modern LLM frameworks — and ship them as reliable backend services.
• Build and operate retrieval systems: ingestion, chunking, embeddings, vector search, and knowledge-graph-backed retrieval where it earns its keep.
• Design AI evaluation pipelines and benchmarks so the team can tell whether an agent, model, or retrieval system is actually getting better — and monitor them in production.
• Architect, implement, and maintain scalable backend services and APIs that other engineers, researchers, and applications build on top of.
• Make senior-level architectural calls — model choice, hosting (Azure OpenAI vs. self-hosted), framework selection, and infrastructure tradeoffs — and mentor other engineers on AI application patterns.
• Develop data pipelines and workflows leveraging Azure (Azure AI Foundry, Azure OpenAI, Azure AI Search, Azure Databricks) and Hugging Face.
• Harden successful prototypes into production: tests, observability, cost and latency monitoring, failure handling, and documentation that let other people trust and reuse them.
• Collaborate directly with researchers, analysts, and program staff to translate fuzzy domain problems into shippable systems for global health and global development.
• Identify knowledge, data, or tooling gaps in the settings in which we work and propose pragmatic solutions.

Requirements

• Bachelor’s degree in a technical field with 5+ years building production software, or equivalent experience.
• Advanced degree is a plus, not required.
• Strong general-purpose backend engineering: you can pick up unfamiliar code, debug across systems, and ship services that hold up in use.
• Proficiency in Python, including for AI work (e.g., PyTorch, Hugging Face, or similar).
• Hands-on experience building LLM-powered applications: retrieval-augmented generation (RAG), agentic workflows, tool use, and prompt engineering at production scale.
• Experience designing and operating backend APIs and services in cloud environments — ideally Azure, but AWS or GCP equivalents are fine.
• Experience building AI evaluations and observability — measuring quality, cost, and latency of LLM systems and acting on the results.
• Hands-on experience with data pipelines and ETL, MLOps/AI Ops workflows, and cloud data services.
• Experience with Git, CI/CD, containerization (Docker), infrastructure-as-code, and broader DevOps practices.
• Comfort making and defending architectural tradeoffs (managed service vs. self-host, fine-tune vs. prompt, agent vs. workflow) and mentoring others through them.
• Comfort working directly with researchers and non-engineers — able to translate fuzzy problems into concrete software, and to push back when the simplest answer is “we don’t need to build that.”
• Track record of taking projects from prototype to something other people rely on.

Qualifications

• Bachelor’s degree in a technical field with 5+ years building production software, or equivalent experience.
• Advanced degree is a plus, not required.
• Strong general-purpose backend engineering: you can pick up unfamiliar code, debug across systems, and ship services that hold up in use.
• Proficiency in Python, including for AI work (e.g., PyTorch, Hugging Face, or similar).
• Hands-on experience building LLM-powered applications: retrieval-augmented generation (RAG), agentic workflows, tool use, and prompt engineering at production scale.
• Experience designing and operating backend APIs and services in cloud environments — ideally Azure, but AWS or GCP equivalents are fine.
• Experience building AI evaluations and observability — measuring quality, cost, and latency of LLM systems and acting on the results.
• Hands-on experience with data pipelines and ETL, MLOps/AI Ops workflows, and cloud data services.
• Experience with Git, CI/CD, containerization (Docker), infrastructure-as-code, and broader DevOps practices.
• Comfort making and defending architectural tradeoffs (managed service vs. self-host, fine-tune vs. prompt, agent vs. workflow) and mentoring others through them.
• Comfort working directly with researchers and non-engineers — able to translate fuzzy problems into concrete software, and to push back when the simplest answer is “we don’t need to build that.”
• Track record of taking projects from prototype to something other people rely on.

Skills

• Experience with vector databases, knowledge graphs, or information architecture for AI applications.
• Experience with fine-tuning, distillation, or other model adaptation techniques.
• Exposure to scientific, public health, geospatial, or climate-related datasets.
• Engagement with the open-source AI community.
• Ability to stand up lightweight interactive demos (Streamlit, Gradio) when needed to show work to non-engineering stakeholders.

Benefits

We provide an exceptional benefits package to employees and their families which include comprehensive medical, dental, and vision coverage with no premiums, generous paid time off, paid family leave, foundation-paid retirement contribution, regional holidays, and opportunities to engage in several employee communities.

Pay

This is a 36-month limited-term position based in Seattle, WA. Relocation will be provided. The salary range for this role is $186,400 to $288,800 USD. We recognize high-wage market differences in Seattle and Washington D.C., where our offices are located. The range for this role in these locations is $203,100 to $314,900 USD. As a mission-driven organization, we strive to balance competitive pay with our mission. New hire salaries are typically between the range minimum and the salary range midpoint. Actual placement in the range will depend on a candidate’s job-related skills, experience, and expertise, as evaluated during the interview process.

Schedule

This is a 36-month limited-term position based in Seattle, WA.

Application Instructions

As part of our standard hiring process for new employees, employment will be contingent upon successful completion of a background check. Candidate Accommodations We’re committed to providing an inclusive and accessible hiring experience for all candidates. If you have a disability or medical condition and need an accommodation at any stage of the application or interview process—such as an ASL interpreter, alternative interview format, or physical accessibility support—we’re happy to help. Please contact HR@gatesfoundation.org with the position number and a brief description of your accommodation needs. Requests will be handled confidentially.

Inclusion Statement

We are dedicated to the belief that all lives have equal value. We strive for a global and cultural workplace that supports ever greater diversity, equity, and inclusion — of voices, ideas, and approaches — and we support this diversity through all our employment practices. All applicants and employees who are drawn to serve our mission will enjoy equality of opportunity and fair treatment without regard to race, color, age, religion, pregnancy, sex, sexual orientation, disability, gender identity, gender expression, national origin, genetic information, veteran status, marital status, and prior protected activity.