Build The Future Of Agentic Automation With Us
We are looking for people who want to change how organisations turn data into decisions and decisions into action.
Mimasa AI builds the layer between an organisation's data and the work that data should trigger. Our customers are procurement teams processing government e-marketplace bids, finance teams handling thousands of supplier invoices, and public sector departments tracking projects across districts. In each case the analysis was never the bottleneck — the last mile between an insight and someone acting on it was.
That is the problem we work on. It means our engineers spend as much time understanding a procurement officer's afternoon as they do tuning a retrieval pipeline, and our designers sit in on customer calls rather than receiving requirements second-hand. If you like problems where the technology is hard and the context matters just as much, you will enjoy it here.
Why Work With Us
We would rather be specific than list perks. Here is what joining the team actually gets you, and what we expect in return.
Competitive Salary And Equity
Every full-time role carries meaningful equity alongside a market-benchmarked salary, so the people building Mimasa AI own a share of what it becomes. Compensation is reviewed twice a year against role, impact and market movement — not tenure.
Flexible Work Arrangements
We are remote-friendly with a hub in Noida. Teams agree on a few overlapping hours for collaboration and keep the rest of the day free for deep work. Where you sit matters far less to us than the quality of what you ship.
Health And Wellness Cover
Health insurance for you and your immediate family, a wellness allowance you can spend on fitness, therapy or preventive care, and genuinely flexible leave — including time off you do not need to justify.
Professional Development Budget
An annual learning budget for courses, certifications, books and conferences, plus paid time to use it. Engineers regularly spend it on distributed systems, applied machine learning and security training.
A Serious Technology Stack
You will work with agentic AI orchestration, retrieval pipelines over enterprise documents, streaming data infrastructure and a React front end used daily by government and enterprise teams. The problems are real and the data is messy in interesting ways.
A Small, Senior Team
We stay deliberately small. That means less process, direct access to founders, and the ability to take an idea from a customer conversation to production within a single sprint.
How We Work
Four principles shape how decisions get made here, from architecture reviews to which customer request we take on next.
Customer Problems Before Technology
We start every project with the workflow a customer is stuck in — a procurement officer drowning in bid PDFs, a finance team keying invoices by hand — and only then decide what to build. Technology choices follow the problem, never the other way around.
Ship Small, Ship Often
Work goes out in small, reversible increments behind clear ownership. We would rather learn from a narrow release used by ten people this week than a broad release used by nobody next quarter.
Write It Down
Decisions, trade-offs and post-incident learnings are written down and searchable. A distributed team runs on good writing, and clear documents make meetings shorter and onboarding faster.
Security Is Everyone's Job
We handle sensitive government and enterprise data. Access controls, audit trails and data minimisation are considered at design time by whoever is building the feature, not bolted on by a separate team afterwards.
Our Hiring Process
Five steps, usually completed within two to three weeks. We tell you where you stand at every stage and never leave an application unanswered.
Application Review
Send us your resume along with a short note on something you have built and what you would want to work on here. A human reads every application and you will hear back within a week, either way.
Introductory Conversation
A 30-minute call covering your background, what you are looking for next, and how we work. It is as much your chance to interview us as ours to learn about you.
Practical Exercise
A timeboxed, paid exercise that mirrors real work — a small feature, a data pipeline, or a design walkthrough. No algorithm puzzles and no take-homes that eat your weekend.
Team And Founder Conversations
You meet the people you would work with day to day, plus a founder. We discuss trade-offs you made in the exercise, how you handle ambiguity, and what support you need to do your best work.
Offer And Onboarding
We move quickly on decisions and are transparent about compensation and equity from the start. New joiners ship something to production in their first two weeks, supported by an onboarding buddy.
Open Positions
Join our growing team and help shape how enterprises automate the work behind their data.
Senior Full-Stack Developer
Build and scale the product surface our customers use every day — from agent orchestration APIs to the dashboards that render their results. You will own features end to end across React, Node.js and cloud infrastructure.
What You Will Do
- Design and ship features across the stack, from data model to interface
- Improve reliability and latency of agent execution and data pipelines
- Work directly with customers to turn operational workflows into product
Data Scientist
Develop the models and evaluation systems behind our forecasting, document understanding and anomaly detection capabilities, and prove they hold up on real customer data.
What You Will Do
- Build and evaluate retrieval and extraction pipelines over enterprise documents
- Design forecasting and anomaly detection models for operational datasets
- Create evaluation harnesses that catch regressions before customers do
UI/UX Designer
Shape how complex, agent-driven workflows feel simple to the analysts, officers and operators who use them under time pressure.
What You Will Do
- Design dashboard, workflow builder and reporting experiences end to end
- Run lightweight research sessions with users in government and enterprise teams
- Extend and maintain our design system across product and marketing surfaces
Careers At Mimasa AI: Common Questions
What It Is Actually Like To Work Here
Joining a small, senior team means fewer layers between an idea and a shipped feature, but it also means more ownership than a larger company would ask of you at the same level. A new engineer typically owns a feature end to end within the first sprint, from talking to the customer about the workflow they are stuck in, through to the interface and the data pipeline behind it. That is deliberate — we think people do their best work when they can see the whole shape of the problem, not just their assigned slice.
Because our customers include government departments and regulated enterprises, a meaningful part of the job involves handling data and access carefully by default, not as an afterthought bolted on before launch. Engineers, designers and data scientists all factor security, audit trails and data minimisation into their day-to-day decisions, which changes the kind of questions we ask in design reviews compared with a purely consumer product team.
We are honest that this pace and ownership level is not the right fit for everyone, and that is fine. People who do well here tend to enjoy ambiguity, prefer writing things down over relying on meetings, and would rather ship something small to ten real users this week than build in isolation for a bigger release next quarter.