Platform Engineer (Mid / Senior / Lead)

Scitara Corporation; Mumbai; On-site; INR 4,000,000 - 6,000,000; Full time

Job summary

Scitara Corporation in Mumbai seeks a Platform Engineer to own features across NestJS/Node.js microservices, gRPC contracts, Kafka event flows, MongoDB data models, and a React UI.

You will work in a small team to ship end-to-end platform capabilities, apply AI-assisted tooling, ensure data integrity and auditability, and mentor teammates. This role blends hands-on coding with architectural decisions and cross-team collaboration.

Qualifications

• Strong TypeScript/Node.js and React experience with non-CRUD, event-driven systems.
• Hands-on with AI coding tools and ability to judge tool outputs.
• Proven track record delivering features to goals, not just tasks.
• Solid engineering fundamentals: design, testing, debugging, and reading unfamiliar code.
• Experience with Git and CI/CD in a team setting.

Responsibilities

• Design and build platform features across NestJS/Node.js microservices, gRPC contracts, Kafka event flows, MongoDB data models, and React UI.
• Build and integrate AI and agentic capabilities into the platform.
• Write code that meets the platform's data integrity and validation requirements.
• Use agentic development tools as the default way of working, and review their output critically.
• Participate in design reviews, code reviews, and Agile ceremonies as a contributor, not an attendee.
• Troubleshoot production and integration issues across service boundaries.
• Senior / Lead: lead technical spikes and architecture decisions; mentor and raise engineering standards.

Skills

TypeScript/Node.js

React

Event-driven design

Distributed data flows

AI coding tools

Code reviews

Tools

NestJS

gRPC

Kafka

MongoDB

Keycloak

AWS

Docker

Kubernetes

Job description

Reports To

Engineering Manager

Experience

5+ years, hiring across levels. Level is set by what you can own end to end, not by years on a resume.

Employment Type

Full-time

About Scitara

Scitara is a global leader in digital transformation for scientific laboratories, enabling connectivity, automation, and data integrity across instruments, applications, and enterprise systems. Our cloud-based DLX platform is used by the world's top pharma, biotech, life sciences, and industrial R&D labs to modernize workflows and accelerate scientific outcomes. Lab informatics is growing 50 to 70% over the next five years, at the exact moment AI is being layered onto scientific data workflows. The software you build here decides how labs around the world adopt that wave.

Role Summary

The DLX platform is a cloud-native, event-driven system of microservices that moves scientific data between instruments, lab applications, and enterprise systems, and increasingly runs AI agents over that data. It has a web UI, but most of the engineering is not web work: it is data processing, orchestration, integration, and backend connectivity in a distributed system. As a Platform Engineer you own features across that whole surface. One week that is a new orchestration capability in a NestJS service talking gRPC and Kafka; the next it is the React screens that expose it; the next it is an agent that acts on the data. You are a generalist by design, and you may bring a specialty on top of that.

How Engineering Works Here

We are a small team with a large product. That shapes everything: You deliver features, not tickets. You get a goal and the context behind it. You work out the plan, the design, the tests, and the rollout. Nobody hands you a task list. AI is part of the job. We use agentic coding tools every day to design, generate, test, and document. You are expected to work this way and to be a sharp reviewer of what the tools produce. You own the result, not the tool. We are regulated. Our customers run validated GxP environments. Data integrity, traceability, and auditability are design constraints, not a checklist at the end. Thinkers and doers. The people who do well here notice problems, propose fixes, get them wrong sometimes, and get them right the next time. They bring ideas back to the team instead of waiting to be told.

Key Outcomes (First 6 to 12 Months)

Ship complete features into production: service, contract, data model, UI where needed, tests, documentation. Take a feature from a one-paragraph goal to a working plan and design without waiting for a task breakdown. Raise the quality of the services you touch: contracts, observability, test coverage, performance. Build or extend AI agent capabilities on the platform. Contribute to how the team uses agentic tooling: prompts, skills, review practices, automation. Senior / Lead: own the design of a platform capability end to end and set the bar for the engineers around you.

Responsibilities

Design and build platform features across NestJS/Node.js microservices, gRPC contracts, Kafka event flows, MongoDB data models, and React UI. Build and integrate AI and agentic capabilities into the platform. Write code that meets the platform's data integrity and validation requirements. Use agentic development tools as the default way of working, and review their output critically. Participate in design reviews, code reviews, and Agile ceremonies as a contributor, not an attendee. Troubleshoot production and integration issues across service boundaries. Senior / Lead: lead technical spikes and architecture decisions; mentor and raise engineering standards.

Must-Have

Strong TypeScript/Node.js and working React. You have built something beyond request/response web APIs: event-driven services, message queues, background processing, distributed data flows. If all you have shipped is Express CRUD, this role will be a hard adjustment. Daily, hands-on use of AI coding tools, and the judgement to know when they are wrong. A track record of delivering features you were given as goals, not as task lists. Solid engineering fundamentals: design, testing, debugging, reading unfamiliar code. Git and CI/CD in a team setting.

Good-to-Have

Our stack specifically: NestJS, gRPC, CQRS, Kafka, MongoDB, Keycloak, AWS. This is a large plus. Building AI agents, working with MCP servers, or integrating LLMs into products. Regulated software: GxP, GAMP 5, 21 CFR Part 11, data integrity. Lab informatics or scientific software: LIMS, ELN, CDS, instrument data. Docker, Kubernetes, cloud-native operations.

Success Indicators

Features reach production without needing the plan written for you. The services you touch are better than you found them. Your use of AI tooling makes you faster and your work more thorough, and your peers pick up what you learn. Colleagues in product, quality, and the connectors team trust your judgement. Senior / Lead: platform decisions get made well when the architect is not in the room.

Why Join Scitara?

Build the system that moves scientific data for the labs developing the next generation of therapies. Work in an engineering culture where AI-native development is the default, not an experiment. Real ownership: features, designs, and decisions are yours. Clear paths into technical leadership and architecture. A global team of engineers, scientists, and customers.