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Baltic Textiles (Mitumba), Kenya Broadcasting Corporation- KBC, Meru University of Science and Technology, World Agroforestry Centre (ICRAF), World VisionProfession (Entry and Basic-level)
Accounting, finance, banking, insurance,Administrative, clerical,Agriculture, fishing, forestry, wildlife,Business, strategic management,Construction,Customer support, client care,Design, arts,Electrical engineering,Energy, power,Engineering, architecture,Food, nutrition,General management, leadership,Government, community development, public services,Human resources,Information technology, software development, data,Installation, maintenance, repair,Legal,Manufacturing, operations, quality,Mechanical engineering,Media, communications, languages,Medical, health,Project, program management,Research, academy,Restaurant, hospitality, travel,Sales, marketing, promotion,Security,Skilled, manual labor,Teaching, training,Telecommunications,Transportation, logistics, driving,
Industry (Entry and Basic-level)
Aeronautics,Agriculture, fishing, forestry,Automotive,Banking, microfinance, insurance,Communications, media, radio, tv,Computers, software development and services,Construction, renovation, maintenance,Consulting, business support, auditing,Data/Research,Education, academic,Energy, utilities, environment,Engineering, architecture,Finance & FinTech,Financial Services,Governmental,Health care, medical,Housekeeping, maintenance,Human resources, talent development, recruiting,Legal, accounting,Manufacturing,Marketing, advertising,Non-profit, social work,Outsourcing, leasing,Real estate,Restaurant, hospitality, travel,Retail, wholesale, FMCG,Telecommunications,Textile, fashion,Transportation, logistics, storage,
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African Leadership X (ALX)
Education + 1 more
Description
Specific ResponsibilitiesProduction AI Products
- Own Ai products in production, stable, observable, with regressions caught by evals before learners find them.
- Take the next prototype from working demo to maintained product, with evals built in from the start rather than bolted on.
- Design the context and tooling architecture for the agents, what is in context, when, and why.
- Build and maintain the service interfaces agents work through, such as the application’s access to the learner’s artifact window.
- Keep long-running, multi-step agents reliable under real-world learner behaviour, with clear failure modes and recovery.
- Build the habit of testing what you ship — eval loops, regression checks, and fast iteration as a default way of working.
- Python & FastAPI: strong, production-grade experience with real users.
- Shipped LLM applications: at least one AI/LLM application you have shipped and can discuss in detail — what broke, how you found out, what you changed. Scale matters less than what you learned from its failures.
- Agent frameworks: working fluency with agent frameworks (we use LangGraph; equivalents fine) and a real point of view on context engineering.
- Testing discipline: the habit of testing what you build.
- AI-native coding with demonstrated harness engineering experience
- Desirable (not required):
- React and full-stack range;
- Langfuse or similar observability; knowledge graphs.
- Educational/Edtech domain experience
- You build with AI, not just use it, proper harnesses, eval loops, and fast iteration.
- You can’t put an interesting problem down.
- You figure things out fast; we don’t need an exact-spec match if you have the base and the initiative.
- You favour non-standard evidence of skill, a portfolio of weird side projects beats a polished CV.
- Courage: Willingness to speak up, challenge the status quo, and embrace new challenges.
- Humility: Openness to learning, seeking help when needed, and a focus on serving others.
- Adventure: A passion for setting ambitious goals, tackling difficult tasks, and finding joy in the journey.
- Initiative: Proactive problem-solving, a sense of ownership, and a willingness to go above and beyond.
- Resilience: The ability to bounce back from setbacks, persevere through challenges, and emerge stronger.
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