About The Role

What you'll be doing

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 hours

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

Nagercoil

Employment typeFull-time

Experience levelFreshers only

Working modelOn-site

Reports toHead of AI

Estimated hiring timeline

Around 2–3 weeks from application to offer.

The team

A small, senior AI pod — engineers, product and QA who own outcomes together.

Hiring process

From application to offer

01

Application submission

Submit your details and resume through our application form.

02

Assessment platform

Complete a practical assessment or short course assigned to you.

03

Assessment review

Our team reviews your submission and shortlists candidates.

04

HR discussion

A Conversation About You, Your Goals, And The Role.

05

Technical interview

A practical session on real ed-tech problems — no whiteboard gotchas.

06

Final selection

A fast, transparent offer built around how you do your best work.

Why join ZionStar

More than a job.

Career growth

Clear progression, real ownership, and the room to grow into the engineer or leader you want to be.

Mentorship

Work alongside senior ed-tech engineers who review your code and invest in your craft.

Real-world projects

Ship software used by real universities, EdTech companies and hundreds of thousands of learners.

Global exposure

Collaborate across continents on projects for organizations worldwide.

Learning opportunities

A generous learning budget and time to use it — we build ed-tech, so we keep learning too.

Engineering culture

Clean architecture, tested code, small senior pods, and weekly shipping. No bureaucracy.

Ready to apply

Tell us about yourself. After you submit, you'll complete a short assessment so we can get to know your work.

Applied AI Engineer (Copilots)