Full Stack Engineer
Indexed description
Website: Visit Website
LinkedIn: Visit LinkedIn
Business Type: Startup
Company Type: Product & Service
Business Model: D2C
Funding Stage: Bootstrapped
Industry: Information Technology
Salary Range: ₹ 5-8 Lacs PA
Job Description
We are building a central operating system for supply chain management and demand
planning for direct-to-consumer (DTC) brands. The platform spans inventory,
forecasting, shipments/imports, and a computational planning core, along with finance features that give clients end-to-end visibility into their supply chain.
You'll join early and work across the stack shipping features end-to-end, shaping the
architecture as we grow, and using modern AI coding tools to move fast without
sacrificing quality.
Since we operate a multi-tenant system, you'll treat data isolation
and correctness as first-class concerns.
What You'll Do
- Build and ship full-stack features across backend (Python/Django) and
- Design and evolve REST APIs, data models, and background workflows.
- Write async and scheduled tasks using Celery, backed by Redis.
- Model and optimize relational data in PostgreSQL, with strict attention to
- Collaborate on architecture decisions as we scale from a monolith toward
- Use AI coding agents (e.g. Claude Code, Cursor, Copilot) effectively in
- Contribute to code reviews, testing, and engineering standards.
- 2–3 years of professional full-stack development experience.
- Solid backend experience with Python and Django (or a comparable
- Frontend experience with React and modern JavaScript/TypeScript.
- Working knowledge of PostgreSQL — schema design, queries, and
- Familiarity with Redis and Celery (or similar caching and async task tooling).
- Hands-on experience using AI coding assistants/agents as part of a real
- Strong sense of ownership, attention to correctness, and clear communication.
- Experience with multi-tenant SaaS architectures and tenant data isolation
- Exposure to supply chain, ERP, logistics, e-commerce, or fintech/finance
- Familiarity with AI/ML workflows (forecasting, planning models) or integrating
- Experience with CI/CD, containerization (Docker), and cloud deployment.
- Testing discipline (pytest, unit/integration testing)
- Early-stage impact: your work directly shapes the product and the architecture.
- Broad scope across a real, complex domain rather than narrow, repetitive tasks.
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