FULLTIME
Applied AI Engineer (Copilots)
KS
keystone software llc
Not specified · onsite · Posted 43d ago
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Section · 01
About this role
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
What we're looking for
Nice to have
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
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
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.
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
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
Nice to have
- Experience shipping production AI features
- Vector databases and retrieval tuning
- Education-technology background
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
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
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.
Sourced from foundit
Section · 02
Skills
RAG promptingvector databasesevalsLLM application experiencePythonRetrieval tuningAPI skills