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A small central-team workspace mid-week: practitioners reviewing module drafts and platform dashboards.

Careers · 2026 hiring

Teach AI to the next million Indian graduates — on the campus where they already study.

We hire three kinds of people: practitioners who can teach, editors who own a curriculum, and operators who turn an MoU into a working campus.

Open roles

7 roles open. 1 more on the roadmap.

Status pills are honest: Open means we're hiring now; Founding cohort means we will hire as the first partner campuses sign; Future hiremeans we won’t open this until we can staff it well.

  • OpenResident faculty

    Resident AI Faculty — ML & Engineering (Track A)

    • On partner campus (rotational)
    • Resident faculty

    Teach agentic systems and applied ML to B.Tech CSE cohorts. Live on a partner campus; teach 6–9 hrs/wk; supervise capstones.

    Apply for this role
  • OpenResident faculty

    Resident AI Faculty — AI for Design (Track B)

    • On partner campus (rotational)
    • Resident faculty

    Teach generative-AI-native design practice to B.Des and BFA cohorts. Strong portfolio + serious AI tool fluency required.

    Apply for this role
  • OpenEngineering & platform

    Senior Engineer — Adaptive Learning Platform

    • Central (Bengaluru / NCR / remote-OK)
    • Engineering & platform

    Build the per-student capability dashboard and adaptive routing engine that powers Principle 9.

    Apply for this role
  • OpenOperations

    Partnerships Lead — South India

    • Central (Bengaluru / NCR / remote-OK)
    • Operations

    Turn serious VC/Dean conversations into signed, staffable, on-campus programs across Karnataka, Tamil Nadu, Kerala, Telangana, AP.

    Apply for this role
  • Founding cohortFounding team

    Chief of Staff — Founding Team

    • Central (Bengaluru / NCR / remote-OK)
    • Founding team

    Right-hand to the founders across academic, ops, and partnerships. High-judgement generalist role.

    Apply for this role

What we hire for

Three properties, in this order. Principle 7, verbatim.

  1. Practitioner background

    Currently building with AI, not just lecturing about it. Has shipped real systems within the past three years.

    In an interview: We will read your code, your designs, or your published work — whichever is the strongest evidence.

  2. Teaching aptitude

    Can explain a transformer to a tier-3 first-year as well as to an IIT senior. Capability is necessary, not sufficient.

    In an interview: We run a teach-back exercise. You pick a concept; we play the cohort.

  3. Cultural fit (humility)

    Believes the B.A. English student deserves the same teaching quality as the B.Tech topper. If you don't, we're a bad fit.

    In an interview: Reference checks weight this above the first two. Speed of disagreement matters more than charisma.

What working here looks like

The actual employee value proposition.

Industry compensation

We pay our resident faculty competitively with industry, not academia. Per ETHOS Principle 7.

On-campus rotation

Resident faculty live where students live. Roles rotate across partner campuses on a 1–2 year cadence.

Curriculum every 6 months

You ship versioned curriculum, not lectures. Outdated content is treated as a defect.

Industry in the room

You teach alongside working AI engineers — every week, on every partner campus.

Apply

Tell us about yourself.

Seven fields. We read every application. We reply within ten working days. The next step, if there is a fit, is a 30-minute call with the hiring lead for the role you applied to.

Equal opportunity. We hire on merit and humility. We do not collect caste, religion, gender identity, or disability data in this form. Reasonable accommodation is available on request via [email protected].

Other paths in

See who already works here. Or read the constitution we hire against.