Job Description

Purpose of Role

The Intermediate AI Engineer focuses on hands-on implementation: building features, wiring up APIs, running experiments, and maintaining AI-enabled tools. They work closely with the Senior Cloud Engineer to turn AI use cases into working solutions and help scale pilots into reliable tools that support teams across AGGP.



This role provides cost-effective delivery capacity, increases the number of AI pilots that can be run per year and helps build AI proficiency among internal AI Builders.

Objectives of Role

I

mplementation & Prototyping

Build and iterate on AI-powered workflows, assistants and internal tools aligned to priority use cases (e.g. program support, grantmaking support, knowledge retrieval, reporting, internal productivity). Implement backend services, scripts or integrations needed for AI pilots and MVPs. Collaborate with the Senior Cloud Engineer on technical design and code reviews.

Experimentation & Evaluation

Design and run experiments on prompts, models and UX flows (e.g. prompt variants, model comparisons, temperature settings). Log, visualise and document experiment results in a way that others can reproduce and understand. Support the development of standard eval processes for AI tools (quality checks, safety checks).

Data & Integration Work

Assist with data preparation for AI tools, including small-scale ETL tasks, preprocessing and cleaning. Integrate AI components with existing systems and APIs, in collaboration with Group IT and data teams.

Maintenance, Support & Continuous Improvement

Help keep AI tools and pilots running smoothly: monitor basic health, fix bugs and address performance issues. Respond to user feedback, triage issues and implement improvements that enhance usability and reliability. Ensure code, configs and documentation are kept up-to-date

Documentation, Knowledge Sharing & Training Support

Maintain clear technical documentation, READMEs and "how-to" guides for AI tools. Support AI training and enablement by preparing demos or simple examples, especially for AI Builders and Champions. Contribute to internal forums such as AI Lunch & Learns and hackathons.

Compliance & Responsible Use

Follow AI and data policies (data classification, acceptable use, tool approval processes). Flag potential risks or issues (e.g. inappropriate data usage, concerning model behaviour) to the Senior Cloud Engineer and Head of AI Strategy & Enablement.

Experience and Qualifications

Education:

Bachelor's degree in Computer Science, Information Systems, Engineering or a related field; or equivalent practical experience.

Experience:

3-5 years of software development, data engineering or related experience. Demonstrated experience building small applications, scripts or integrations that solve real user problems. Exposure to AI/ML or LLMs (e.g. using APIs like OpenAI, Azure OpenAI, Anthropic, or similar) is strongly preferred. Experience in nonprofit, education or social impact environments is an advantage but not required.

Competencies

Technical Proficiency:

Comfortable with at least one general-purpose programming language (e.g. Python, JavaScript/TypeScript). Familiarity with calling APIs, handling JSON, and working with SDKs for AI/LLM providers. Basic understanding of cloud services (Azure and/or AWS), especially serverless functions, storage and identity. Experience with version control (Git), and basic CI/CD pipelines. SQL and/or basic data transformation skills are a plus.

Behavioural Competencies and Technical Skills:

Curious, proactive learner with a strong interest in AI and how it can be applied responsibly in AGGP's context. Practical, delivery-focused and comfortable iterating based on feedback. Collaborative and open to pairing with Senior Cloud Engineer, AI Builders and domain experts. Able to communicate clearly with non-technical colleagues about what tools can and cannot do. * Values AGGP's mission and ethics, particularly around fairness, transparency and responsible use of data and AI.