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
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.
