Applied AI Engineer (Global Health)

Location: Remote within the United States, with occasional travel. U.S. citizenship is required by the federal government contract.

Salary: $98,614–$167,644 per year.

Company

hirify.global is a global advisory and technology services provider combining domain expertise with technology to address complex client challenges.

What you will do

• Design and build LLM pipelines and agent systems for survey reporting, natural-language data analysis, questionnaire translation, and field support.
• Build evaluation harnesses, expert-ground-truth test sets, automated and human grading workflows, and regression tests.
• Route workloads across models based on reasoning complexity, volume, cost, latency, and data-residency requirements.
• Manage inference costs through token tracking, context limits, prompt caching, batch processing, and model-selection analysis.
• Connect models to data services and full-stack applications, review agent-generated code, and own production quality.
• Monitor systems, analyze errors, document positive and negative results, and transfer tools to partner-country institutions.

Requirements

• Bachelor’s degree in Computer Science, Engineering, or a related field, or equivalent experience.
• At least 4 years of professional software development experience, including production LLM-powered systems used by real users.
• U.S. citizenship is required.
• Proficiency in Python or another modern programming language such as JavaScript/TypeScript or Go.
• Hands-on experience with frontier-model APIs, tool use, retrieval-augmented generation, cloud platforms, agent frameworks, and AI evaluation tooling.
• Experience designing LLM evaluations and using agentic coding tools to specify, review, test, and own production code.

Nice to have

• Experience with expert-grounded, structured-data, tabular-data, or statistical-analysis tasks.
• Experience with multilingual or low-resource-language NLP, translation, speech, or open-weight models.
• Experience with sensitive or regulated health data, human-subjects research, model governance, monitoring, or responsible AI.
• Experience in global health, international development, or low- and middle-income country settings.
• Open-source contributions, published evaluations, or technical writing about systems built.

Culture & Benefits

• Remote work within the United States with occasional travel.
• Collaboration across technical, research, government, and partner-country stakeholders.
• Emphasis on candid communication of uncertainty, limitations, and negative results.
• Full-time employment; the position is contingent upon program funding.