Associate, CTO's Office

About the Company

Adalat AI is building an end-to-end justice tech stack that automates manual and clerical pain points in courtrooms, giving judges back time to focus on what matters most: decision-making and delivering justice. Our solutions - from AI-powered transcription in Indian languages to case-flow management and document navigation - are now deployed across 9 states, covering nearly 20% of India’s judiciary. Backed by leading technology companies and funders, and incubated at MIT and Oxford, Adalat AI is working to eliminate judicial delays and expand access to timely justice. Founded by a team with backgrounds in law, technology, and economics from Harvard, Oxford, MIT, and IIIT Hyderabad, we are scaling rapidly across India and the Global South.

Role Overview

We are hiring an Associate in the CTO’s Office — the operational and technical right hand to the CTO as he builds out the technology org.

This is not a rotational generalist slot and it is not a traditional chief-of-staff role. It is a hybrid engineer-operator role for someone who can write software, read a codebase, reason about a product, and still happily spend a Tuesday afternoon cleaning up a deployment tracker or coordinating an onboarding schedule. You will sit close enough to the CTO to absorb how a technology org actually runs — from architecture reviews to hiring loops to partner escalations — and you will ship real tools, not just manage spreadsheets.

The best version of this person is a strong early-career software engineer who is bored of pure feature work and wants breadth, context, and proximity to decision-making — the kind of person who will learn more in a year here than they would in three years on a product team elsewhere. If you want to eventually start a company, lead engineering, or become a CTO yourself, this is a front-row seat.

Key Responsibilities

Build internal software and automations. You will ship real tools — not just “vibe code.” Internal dashboards that unify Airtable, partner data, and deployment telemetry. Scripts that pull from Slack, Gmail, Granola, and Linear and route the important bits to the right person. Lightweight services that automate onboarding, partner health checks, and weekly reporting. You will use AI-assisted tooling (Cursor, Claude Code, v0, Replit) aggressively, but you will also read your own diffs and understand what you shipped.
Develop a deep working understanding of the product. Transcription pipelines, courtroom deployments, model training, the data privacy envelope, the court tech stack itself. You will sit in architecture reviews, read PRs and design docs, and be expected to hold an informed conversation about any part of the system within a few months. You do not need to write production code in the core stack — but you should be able to follow it, contribute small patches, and ask good questions.
Own partnerships data infrastructure. Deployment trackers, court onboarding pipelines, partner health dashboards, adoption metrics. You will design the data models (Airtable + Excel + Python when needed), keep them clean, and build the reporting that the leadership team runs on.
Run tech-team HR operations. Hiring pipelines, onboarding schedules, performance review logistics, team rituals. You will build the systems that make these things run on rails, then automate the parts that can be automated.
Be the bridge between technology and partnerships. Deployment requirements flow one way; ground-level feedback flows the other. You are the person who makes sure nothing gets lost in translation.
Maintain the CTO’s Office knowledge base. Decision logs, roadmap trackers, meeting notes, internal documentation. The org’s institutional memory lives with you.
Hunt for inefficiencies and ship fixes. Spot a broken workflow, propose an AI-powered or tool-built solution, get buy-in, ship it. Measure whether it actually saved time.
Prepare briefs and data summaries for leadership, board, and stakeholder conversations. Clear writing, real data, sharp framing.

Qualifications

0–3 years of experience, ideally with some exposure to engineering, a fast-growing startup, or a high-intensity consulting / analyst role. Fresh graduates with strong proof-of-work are welcome.
A computer science, engineering, math, physics, or equivalent technical background is a plus, but not a hard requirement. What matters is whether you can write software and reason about systems.
Demonstrable code. A GitHub profile, a deployed side project, a meaningful open-source contribution, or a portfolio of internal tools / automations you have built. We will read it. Generic resumes with no artifacts will not make the cut.
Working knowledge of at least one general-purpose programming language (Python, TypeScript/JavaScript, or Go preferred). You should be able to write a small service, wire up an API integration, or build a dashboard end-to-end.
Fluency with modern AI dev tooling — Claude, Cursor, Claude Code, ChatGPT, v0, Replit, and similar. You have built things with them, not just chatted.
Strong Excel / Google Sheets and Airtable — you can model data, build pivots, and construct structured trackers without supervision.
Excellent written communication. A tight email, a clear Slack message, a well-structured brief. Writing is thinking.
Comfort with ambiguity and context-switching. You move between a data cleanup, a hiring brief, and a new internal tool in the same morning without losing the thread.

What You Will Achieve in a Year

You will have shipped a handful of internal tools and automations that the team actually uses every week — and you will be able to measure the hours saved.
You will have deep working understanding of the Adalat product, the model training pipeline, and the court deployment architecture.
You will own the partnerships data infrastructure — trackers, dashboards, reporting — that leadership runs on.
You will have designed and run structured HR and operational processes for the tech team that did not exist before you joined.
You will have earned the trust to represent the CTO’s Office independently in cross-functional and stakeholder conversations.
You will be a significantly better engineer, operator, and thinker than when you started — because you will have had a year of direct exposure to how a deep-tech nonprofit actually gets built.