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

- 3 years in software or ML engineering

- 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 solid 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 level3 years

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) (Agasteeswaram)
🏢 KeyStone Software
📍 Agasteeswaram