Background information about the job or company (e.g., role context, company overview)

IDinsight is an international development organization that helps policymakers and managers make socially impactful decisions using rigorous evidence. We carefully tailor a wide range of analytical and quantitative tools to enable our clients to design better policies, rigorously test those ideas, and take informed action at scale to improve lives. Our servi...

Responsibilities or duties

As an AI engineer on the AI Transformation team, the day-to-day work may include:

• Working with IDinsight teams and external clients to understand their current processes and pain points and identifying which of these can be solved with AI-powered tools.
• Working across business functions internally and externally — from research to finance to operations to programmatic challenges — to find ways of creating efficiency gains through AI tools and automation.
• Building and deploying user-facing AI applications: from LLM-based pipelines and agents to workflow automations and internal tools.
• Designing, testing, and iterating on LLM-based solutions — prompt engineering, retrieval-augmented generation, multi-step agent architectures, and API integrations.
• Working across the full stack — frontend, backend, and deployment — to ship tools that people actually use.
• Building dashboards, usage tracking, and analytics to measure the impact of deployed tools.
• Synthesising, visualizing, and communicating results internally with other teams as well as externally with clients: dashboards, plots, interactive viz, presentations and reports.
• Writing blog posts or presenting on lessons learned.

Qualifications or requirements (e.g., education, skills)

Required Technical Qualifications

• 2–4 years of professional experience in software engineering, AI/ML engineering, or a closely related technical role.
• Proficiency in Python is required — including web frameworks, API development, and scripting. Please do not apply if you are not comfortable building production-quality Python applications.
• Experience building solutions using Large Language Models. This includes designing prompts, building LLM-based pipelines, retrieval-augmented generation systems, or developing applications that use LLM APIs.
• Ability to work across the full stack: backend (APIs, data pipelines), frontend (basic UI/UX for internal tools), and deployment (containerization, cloud services).
• Working knowledge of SQL and comfort working with structured data.
• Familiarity with version control (Git), CI/CD practices, and writing clean, reproducible code.
• B.S./B.S.E. degree in Computer Science, Software Engineering, Applied Math, Data Science, or a similar technical field.

Experience needed

2–4 years of professional experience in software engineering, AI/ML engineering, or a closely related technical role.

Any other provided details (e.g., benefits, work environment, team info, or additional notes)

Career Development

Professional development for our technical roles is essential for IDinsight's long-term impact. With support from IDinsight leadership, the employee will maintain self-directed professional development plans and will be given "stretch" opportunities designed to strengthen their professional skills. Real-time feedback and structured reviews are regularly provided to maximize each team member's expertise. IDinsight's entrepreneurial culture allows roles and career progression to be tailored to individual strengths, interests, and goals. Employees have the opportunity to increase responsibilities, and high performers will have the opportunity to move up in the organization along technical, managerial, or client-facing paths.

• Working with IDinsight teams and external clients to understand their current processes and pain points and identifying which of these can be solved with AI-powered tools.
• Working across business functions internally and externally — from research to finance to operations to programmatic challenges — to find ways of creating efficiency gains through AI tools and automation.
• Building and deploying user-facing AI applications: from LLM-based pipelines and agents to workflow automations and internal tools.
• Designing, testing, and iterating on LLM-based solutions — prompt engineering, retrieval-augmented generation, multi-step agent architectures, and API integrations.
• Working across the full stack — frontend, backend, and deployment — to ship tools that people actually use.
• Building dashboards, usage tracking, and analytics to measure the impact of deployed tools.
• Synthesising, visualizing, and communicating results internally with other teams as well as externally with clients: dashboards, plots, interactive viz, presentations and reports.
• Writing blog posts or presenting on lessons learned.

• Proficiency in Python (web frameworks, API development, scripting)
• Experience building solutions using Large Language Models (prompt engineering, LLM-based pipelines, retrieval-augmented generation, LLM APIs)
• Full stack development (backend, frontend, deployment)
• Working knowledge of SQL
• Familiarity with version control (Git), CI/CD practices

• B.S./B.S.E. degree in Computer Science, Software Engineering, Applied Math, Data Science, or a similar technical field.