AI Engineer

Teneo Online School

AI Engineer building AI-enabled products for a global EdTech company. Collaborating with engineers and education partners to enhance learning outcomes.

Posted 6/25/2026full-timeRemote • 🇱🇹 LithuaniaJuniorMid-LevelWebsite

Tech Stack

Tools & technologies

CloudJavaScriptNode.jsPythonTypeScript

About the role

Key responsibilities & impact

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 productionise 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.

Requirements

What you’ll need

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.
Strong ownership, debugging and problem-solving skills.
Clear written and spoken English.

Benefits

Comp & perks

Work with education partners and internal stakeholders
Build evaluation approaches
Collaborate with Backend Engineers
Use AI-assisted development tools appropriately
Write clean, tested and maintainable code

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools

data scienceapplied AImachine learning engineeringPythonTypeScriptNode.jsprompt designstructured outputsAI orchestrationevaluation of AI quality

Soft Skills

problem-solvingownershipself-directed approachcommunicationcollaborationdebuggingbalancing experimentationunderstanding stakeholder needstesting assumptionsimproving product quality