You will build LLM-powered copilots and chatbots grounded in our clients’ course content — with the retrieval, guardrails and evaluation that make them safe and genuinely useful in education.
Key responsibilities
Your day to day
Build RAG-based copilots grounded in client content
Design guardrails, evals and quality monitoring
Embed AI experiences into LMS and portal products
Iterate from real usage and feedback
Requirements
What we're looking for
Solid software or ML fundamentals — freshers welcome
Hands-on LLM application experience (RAG, prompting, evals)
Strong Python and API skills
A product mindset and care for user trust
Preferred Qualifications
Nice to have
Experience shipping production AI features
Vector databases and retrieval tuning
Education-technology background
Benefits
What we offer
Competitive salary, reviewed yearly
Fully remote with flexible schedule
Generous learning & development budget
Paid time off and wellbeing support
Top-tier equipment of your choice
Global, inclusive engineering culture
Learning opportunities
How you'll grow
How to ship trustworthy AI in a high-stakes domain
Retrieval and guardrail patterns that hold up in production
Turning AI prototypes into dependable products
FAQ
Questions, answered
Is this role fully remote?
Yes — we are remote-first and hire globally. You can work from wherever you do your best work, with overlap hours for collaboration.
What does the hiring process look like?
Application, a practical assessment, assessment review, an HR discussion, a technical interview, and a final decision — typically wrapped up in 2–3 weeks.
Do I need education-technology experience?
It helps, but it is not required. We value strong engineering and a genuine interest in education; we will get you up to speed on the domain.
Who will I report to?
You will report to the Head of AI, and work day to day inside a small, senior pod.
DepartmentAI
LocationOn-site
Nagercoi
📌 Applied AI Engineer (Agasteeswaram)
🏢 KeyStone Software
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