Machine Learning Ops Engineer

Experience: 3–5 years

About the role

We're building an AI-powered intelligence platform for C-suite management — turning raw data into action instead of static reports. It pairs domain expertise across Indian manufacturing set up with AI-generated insights to surface what matters most, right where the user can act on it. You'd be joining as we take this from a working build toward our first phase of the project on our pathway to creating business value implying the power of data enabled intelligence and inferences.

What you'll actually do

• Design and build the Postgres schema for a multi-tenant financial product (clients, transactions, invoices, computed metrics, audit logs) — and get the access-control model right, since this is financial data
• Build the backend API (Node.js/Fastify or Python/FastAPI) for the performance dashboard deployment using real time, queried data
• Port document-parsing logic (PDF/JSON ingestion of documents/scans/images to run server-side, reliably, on upload
• Deploy and operate the infrastructure: Railway/Render, Supabase/Postgres, Cloudflare, secrets management — you're the one who gets paged if something goes down
• Build and harden an AI proxy layer (calling Claude/Anthropic's API) with per-client rate limiting and cost controls — the key never touches the frontend
• Set up CI/CD, staging environments, and basic monitoring (Sentry, uptime checks) from week one, not as an afterthoughtYou should have
• 3+ years building and shipping backend services in production, not just in tutorials
• Real experience with a relational database (Postgres strongly preferred) — schema design, migrations, query performance
• Comfort deploying and owning infrastructure yourself (Railway, Render, AWS, or GCP) — you don't need a dedicated DevOps team to get something live
• Experience with API design and auth/access-control patterns, ideally in a multi-tenant context
• Solid instincts around secrets management and not committing credentials to git (yes, this needs to be said)Nice to have
• Experience integrating LLM APIs (Anthropic, OpenAI) in a production backend
• Exposure to fintech, accounting, or any regulated-data domain