A mentored internship for fresh graduates who want real production work, not busywork. Build in GoLang, Rust, Python, NodeJS & TypeScript, Data Science, AI & Machine Learning, Post-Quantum Cryptography, Agentic AI, Cybersecurity & InfoSec Compliance, VAPT and Modern UI/UX — guided by Dr. Sougata Pal and his team, with 18+ years of industry experience behind every review.
A Degree Alone No Longer Starts a Career
Graduates leave university fluent in theory and unprepared for the codebase. The gap is not intelligence — it is never having shipped anything a stranger depends on. Meanwhile the fields that matter most (post-quantum cryptography, agentic AI, offensive security) move faster than any syllabus can follow. This internship closes that gap by putting you on real work, reviewed by people who have done it for 18+ years.
You pick a domain, you get an assigned mentor, and you ship code that other people rely on — then you see exactly where that work leads in the corporate growth path.
Production tickets from day one — no synthetic exercises, no shadowing from the back of the room
Every pull request reviewed by an engineer who has shipped the same thing at scale
Twelve domains to choose from, including fields most graduates never touch until year five
A published growth ladder, so you always know what the next rung asks of you
A verifiable QSECS certificate and a portfolio of work you are allowed to talk about
We select on curiosity and rigour, not on the label of your degree. If you are graduating from any of the programs below — or have graduated within the last two years — you are eligible to apply.
Computer Science, IT, Electronics, or any engineering branch with a genuine appetite for building software and breaking it responsibly.
Strong programming fundamentals, data structures and algorithms. A natural fit for the systems, backend and product engineering domains.
Lattices, number theory and probability are the bedrock of post-quantum cryptography and machine learning. Mathematicians thrive here.
Quantum mechanics is not a metaphor in our work. Physicists bring exactly the intuition the post-quantum track needs.
Application development, databases and web platforms — a direct on-ramp into the product, data and modern UI/UX engineering domains.
Advanced application architecture and systems coursework. Interns often enter at a deeper starting scope than the standard first stage.
Specialisation already in hand. Bring it to cryptography, machine learning or security engineering and go deep from week one.
Polytechnic diplomas and vocational certificates in computing or electronics. Demonstrated skill counts for more here than the length of the program.
Computing, mathematical or physical sciences. Research-track interns work on the problems at the edge of what is currently published.
No prior industry experience is expected. What we look for is one language you know well, one problem you cared enough to solve unprompted, and the willingness to be reviewed.
Dr. Sougata Pal brings 18+ years of industry experience across cybersecurity, cryptography, distributed systems and applied AI. He leads the internship personally, supported by a team of senior QSECS engineers who each own a domain group. You are never left to guess.
A named mentor for your domain from your first day — not a rotating pool
Weekly one-to-one review of your code, your design decisions and your blind spots
Fortnightly deep-dive sessions led by Dr. Pal on the research behind the domain
An honest mid-point assessment against the growth ladder, with a written plan
An intership experience letter and, for the strongest interns, a full-time offer based on project
Choose the domain that pulls at you. Each one sits inside a group with its own mentor, its own real project, and its own mapped route through the corporate hierarchy.
Concurrent services, gRPC APIs and the microservices that carry production traffic.
Memory-safe systems programming where correctness and performance are both non-negotiable.
The connective tissue — services, tooling, automation and every data and ML pipeline we run.
Typed, end-to-end services — Node APIs, build tooling, and the type system that keeps a large codebase honest.
Turning raw telemetry into the answers that change what a business does on Monday.
Statistical modelling, experiment design and inference you can defend in front of a sceptic.
Training, evaluating and deploying models that hold up outside the notebook they were born in.
Retrieval pipelines, tool-using agents, and the guardrails that keep autonomy bounded.
ML-KEM, ML-DSA, SLH-DSA and hybrid schemes — implemented, benchmarked and migrated.
Threat modelling, detection engineering and incident response — plus the control frameworks (SOC 2, ISO 27001, NIST CSF) that hold a defence to account.
Vulnerability assessment and penetration testing on live engagements, alongside QRedSentinel.
Design systems, accessible components and interfaces that make hard software feel obvious.
Every domain group maps onto the same five-stage corporate hierarchy — from your first reviewed commit to owning the architecture. Select a group to watch its path build.
Ship reviewed Go, Rust and Python modules against real tickets. Learn the codebase, the tests and the release path.
Take a feature from ticket to production on your own, including its tests, telemetry and rollback plan.
Own a service end to end — its API contract, its performance budget, its on-call rotation.
Design across services, set the technical direction for a squad, and grow the engineers behind you.
Own the platform architecture and the engineering org that builds it. Decide what gets built at all.
Clean real data, build baseline models and evaluate honestly. Learn why the notebook is never the product.
Build the pipelines and feature stores that keep models fed, and ship your first model to production.
Own a model in production — its evaluation, its drift, its retraining and the decision it drives.
Set the modelling strategy for a product area, lead agentic and RAG systems, and mentor the bench.
Own the AI platform, the data strategy and the governance that keeps autonomous systems accountable.
Supervised reconnaissance, scanning and finding triage. Learn to write a report an engineer will act on.
Run assessments end to end, implement PQC primitives, and defend your severity ratings in review.
Own client engagements, build the detections, and lead cryptographic migration work.
Direct the red team, set the threat model for an organisation, and own its quantum-readiness roadmap.
Own the security posture of the whole business — architecture, compliance, budget and accountability.
Build accessible components against a design system. Learn that an interface is a contract, not a picture.
Ship whole screens, own their accessibility and performance, and test them on real users.
Own an entire product surface, from the interaction model down to the render budget.
Own the design system itself, and the standard every other engineer builds interfaces against.
Own how the company's software feels to everyone who touches it, and the craft bar that holds it there.
Timelines are typical, not fixed. Interns who consistently exceed the scope of their stage move faster — several have reached Stage 03 within three years.
A deliberate ramp from your first reviewed commit to a capstone you present to the whole team.
Environment, codebase, review culture and the fundamentals of your chosen domain. Your first merged pull request lands in week two.
Real tickets on real systems with a mentor beside you. Weekly one-to-ones, fortnightly deep-dives with Dr. Pal.
You own a feature outright — design, implementation, tests, telemetry and release. The mid-point assessment sits here.
Build and present a capstone to the team. Strong performers receive a full-time offer at Stage 02 of the growth path.
Full-time and part-time schedules are both available; part-time interns run the same four phases across nine months.
What graduates ask us before they apply.
No. This program exists precisely for people who have none. What we do expect is fluency in at least one programming language, and evidence — a project, a paper, a contribution — that you have solved a problem nobody assigned you.
Yes. B.Sc graduates in Mathematics and Physics are actively encouraged to apply, particularly for the post-quantum cryptography and machine-learning domains where that background is a genuine advantage rather than a gap to be closed.
You may express interest in several, and the application form lets you select as many as you like. You will be placed in one primary domain so your work has depth, but cross-domain contribution is common — security interns routinely write Rust, and AI interns routinely touch the UI.
The internship carries a stipend, and both remote and onsite participation are supported. Exact terms are confirmed during the interview stage and depend on your schedule and location.
It can. Interns who complete the capstone and consistently meet the Stage 01 bar are considered for a full-time offer entering at Stage 02 of the growth path. There is no quota, and no guarantee — the assessment is the assessment.
An application, a short take-home relevant to your chosen domain, and two conversations — one technical, one with Dr. Pal about how you think. We respond to every application within two weeks.
Tell us who you are and which domains pull at you. Every application gets a response within two weeks — including the ones we cannot take forward.