AI Engineer
WFA Digital Insight
The demand for AI engineers in the EdTech sector has seen a significant surge, with a 25% increase in job postings in the last year alone. As online learning continues to grow, companies like Teneo Online School are at the forefront of developing innovative AI-powered solutions. With the rise of remote work, professionals with expertise in digital skills are in high demand. To succeed in this role, candidates should possess a strong foundation in machine learning, data science, and software engineering, as well as excellent collaboration and communication skills. Before applying, candidates should be aware of the company's commitment to building trustworthy AI capabilities and its focus on improving learning outcomes at scale.
Job Description
About the Role
The AI Engineer will play a crucial role in Teneo Online School's Technology Team, responsible for designing and building AI-enabled features for various education products. This includes assessments, tutoring, and other learning tools that support better learning outcomes. The ideal candidate will have a strong background in machine learning, data science, and software engineering, with experience in building AI-enabled features and prototypes.As an AI Engineer at Teneo Online School, you will work closely with cross-functional teams, including Product and Backend Engineers, educators, and education partners. Your primary focus will be on developing reliable, measurable, and useful AI-powered product features that enhance the learning experience. You will also collaborate with stakeholders to understand real assessment and learning workflows, test ideas against real use cases, and take successful approaches into production.
Teneo Online School is a global EdTech company that is committed to building a suite of AI-enabled products to support better learning outcomes at scale. As an AI Engineer, you will be part of a team that is passionate about harnessing the power of AI to improve education.
What You Will Do
- Design and build AI-enabled features for various education products, from assessments to tutoring
- Work with education partners and internal stakeholders to understand assessment practices, quality expectations, and real-world constraints
- Build evaluation approaches that measure output quality, consistency, usefulness, and failure modes
- Develop retrieval, prompt-management, orchestration, and structured-output workflows where appropriate
- Integrate LLM APIs, AI services, and education data into reliable product capabilities
- Design practical human-review, control, and escalation workflows for AI-supported decisions
- Improve the reliability, latency, cost, and quality of AI services in production
- Build prototypes quickly, test them against real education use cases, and productionize successful approaches
- Develop suitable guardrails, monitoring, and auditability for AI outputs
- Work with Backend Engineers on service architecture, data handling, integrations, and scalability
- Work with Product Engineers to ensure AI features are understandable, useful, and trustworthy for teachers and students
What We Are Looking For
- 2+ years of professional data science, applied AI, or machine-learning engineering experience
- Experience building AI-enabled features, prototypes, or production applications using LLM APIs or related AI services
- Strong programming ability in Python, TypeScript/Node.js, or similar languages
- Experience with prompt design, structured outputs, retrieval workflows, AI orchestration, or agentic workflows
- Experience evaluating AI quality, reliability, and safety beyond informal manual testing
- Solid understanding of APIs, databases, cloud services, and production software architecture
- Ability to balance experimentation with disciplined engineering, testing, privacy, and security standards
- A self-directed approach to investigating new methods, testing assumptions, and improving product quality
- Comfortable working with non-technical stakeholders and education partners to understand the real problem behind a feature request
Nice to Have
- Experience with retrieval-augmented generation, embeddings, vector databases, or document-processing pipelines
- Experience designing evaluation datasets, test harnesses, quality metrics, or human-review workflows
- Experience with data pipelines, ETL, and production-level data science
- Experience with privacy, security, auditability, or responsible-AI practices
- Experience with modern cloud platforms and containerized application deployment
Benefits and Perks
- Opportunity to work on cutting-edge AI-powered education products
- Collaborative and dynamic work environment with a global team
- Professional development opportunities and support for continuous learning
- Flexible working hours and remote work arrangements
- Access to the latest technologies and tools
- Competitive compensation package and benefits
How to Stand Out
- Tip: Showcase your experience with AI-enabled features and prototypes in your portfolio, highlighting your ability to design and build reliable and useful AI-powered product features.
- To stand out, demonstrate your understanding of the education sector and the role of AI in improving learning outcomes.
- Be prepared to discuss your approach to evaluating AI quality, reliability, and safety, and provide examples of your experience with prompt design and structured outputs.
- Familiarize yourself with the company's products and services, and be prepared to discuss how your skills and experience align with their goals and mission.
- During the interview process, ask questions about the company's approach to responsible AI practices and their commitment to building trustworthy AI capabilities.
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