Full Stack Developer (AI Products)

Full Stack Developer (AI Products)

Build complete applications — and the AI features inside them — for MGRM's education, healthcare, compliance and citizen-facing platforms

This is a full stack engineering role on products that are adding AI. You will build application features across the stack, and you will build the AI capabilities that go into those features. We work with AI coding tools day to day and expect you to already do the same.

About MGRM Group

Hitachi MGRM Net Limited is the technology and digital services arm of MGRM Group, a multi-domain organization working across education, healthcare, pharmaceutical, insurance, agriculture and transportation. Built on three decades of research, the group's e-governance architecture and framework is deployed across multiple countries, and Hitachi MGRM Net delivers domain applications, solutions and services to public and private sector clients in India, implementing systems licensed from parent company MGRM Inc, USA. Our product suite serves institutions and citizens at scale — hospitals, schools, colleges and government departments — and we are now building AI capabilities into it.

What You Will Build

This role has three areas of responsibility, across one or more product lines.

1 Full Stack Application Development

Build features end to end, from database to screen.

• Build application features across the stack — API endpoints, business logic, data models, and the React front-end users work with.
• Design schemas and write queries that hold up under production data volumes.
• Build AI features into the products — search, extraction, summarization, and assistant-style interfaces that call language models.
• Test AI output for reliability before it goes in front of users.
• Integrate with other services and products in the suite where features need shared data.
• Work from written specifications and raise it when a specification is wrong.

2 AI-Assisted Engineering Practice

Work with AI coding tools, and review what they produce.

• Use AI coding agents as part of your normal workflow, on well-scoped pieces of work.
• Review generated code properly — catch what looks correct but isn't and notice invented APIs and misused libraries.
• Know when the tool is the wrong choice and write the code yourself.
• Keep the architecture coherent regardless of how much of it was generated.

3 Quality, Security and Documentation

• Write unit and integration tests (Jest or Vitest) and end-to-end tests where needed (Playwright or Cypress).
• Follow the lint and CI setup — ESLint, Prettier, GitLab CI.
• Validate API input. No secrets in code.
• Document your APIs and keep the README current.
• Review pulls requests.

Experience Framework

Total: 3–5 years. The core skill is full stack development. Within that, we want at least one AI feature you have taken to production.

What We Mean

Full Stack Development (core)

3–5 yrs

Production experience across the stack — Node.js backend services, relational data modelling, and react front-end work.

Node.js & TypeScript

3+ yrs

Strong JavaScript and TypeScript, with Express or Fastify. Comfortable with async patterns, error handling and API design.

PostgreSQL

2+ yrs

Schema design, indexing, query performance, and judgement about what belongs in the database rather than in application code.

React

2+ yrs

Component design, state management, and enough CSS and product sense to build a screen someone can actually use.

AI Feature Development

1 yr

At least one feature calling a language model, shipped to production — RAG, extraction, summarization, or an assistant. One is enough.

AI-Assisted Development

Current

Day-to-day fluency with AI coding tools, and honesty about where they help and where they don't.

Education / Healthcare (bonus)

Any

Exposure to student records, admissions, hospital or clinical systems, or the regulatory context around them.

On the AI experie**nce: one shipped feature that calls a model is the bar — a search over your own documents, an extraction pipeline, a summarizer. We are not asking for research work or model training. What we want to hear is how you made the output reliable enough to ship.

Technical Skills

Core Development

AI / LLM

Domain & Process

• Node.js with TypeScript

• Express or Fastify

• React

• PostgreSQL

• REST API design

• Git-based workflows

• Unit and integration testing

• Docker (as a consumer)

• LLM API integration

• Prompt design and iteration

• Retrieval-augmented generation

• Vector search (pgvector or similar)

• Structured output from models

• Evaluating output quality

• AI coding agents

• Education or healthcare software (bonus)

• Regulated data handling (bonus)

• DPDP Act 2023 awareness

• Agile delivery

• Documentation discipline

Also, useful

Message queues, caching, CI pipeline authoring, API testing tools, basic Kubernetes literacy (deploy and read logs, not administer)

Who Will Thrive in This Role

• You are a strong generalist — comfortable moving between a query plan, an API contract and a React component in the same day.
• You have built at least one AI feature and hit the real problems: unreliable output, latency, cost, context limits.
• You already work with AI coding agents and have a clear view of what they are good at.
• You read code carefully, including code you did not write.
• You are comfortable working from a specification, and comfortable saying when it is wrong.
• You can sit with a non-technical user, understand what they actually need, and build something they can use.

What We Offer

Scope

Full ownership of features across the stack, on products with real institutional users.

AI work

Applied AI feature development on live products, not proof-of-concept work.

Tooling

AI coding tools supported and expected as part of normal development.