Position: Sr. Backend Engineer
Location: Bangalore
Working Days: 5(Mon-Fri)
Experience Required: 2-5 Years
Most systems work at a low scale. Very few survive real production load, complex workflows, and enterprise edge cases. We are building a platform that must:
- Scale from 500K 20M+ interactions/month
- Handle complex insurance workflows reliably
- Become easier to deploy as it grows, not harder
This role exists to build the backend foundation that makes this possible.
You will not just write services. You will design and own core platform systems.
- Scale from 50K 2M+ interactions/month
- Ensure:
- High availability
- Low latency
- Fault tolerance
- Avoid large rewrites , build systems that evolve cleanly
- Design a flexible system with:
- States
- Stages
- Cohorts
- Dynamic workflows
- Ensure workflows:
- Handle edge cases reliably
- Can be configured easily
- Move from: Hardcoded flows configurable execution engine
- Design data models for:
- Policy states
- Claim workflows
- Consent tracking
- Ensure the system works across:
- Multiple insurers
- Multiple use cases
- Build a platform-first data layer, not use-case-specific hacks
- Ensure workflows and data models are:
- Easy to configure
- Easy to launch
- Reduce friction for:
- Product teams
- Deployment teams
- Build a data layer that:
- Improves with every deployment
- Captures structured signals
- Ensure data becomes a long-term edge, not just storage
- Participate in on-call rotation across 3 engineers
- Ensure:
- Incidents are handled quickly
- Root causes are fixed permanently
- Build systems where reliability is shared, not individual
- Platform scales to 2M+ interactions/month smoothly
- Workflow engine supports complex, dynamic use cases
- Data layer enables fast deployment across accounts
- Edge cases are handled without constant firefighting
- System becomes easier to use as it grows
- Production issues are rare and predictable
- You have 2–5 years of backend engineering experience
- You have built:
- Scalable systems
- Distributed services
- You think in:
- Systems
- Data models
- Trade-offs
- You are comfortable owning:
- Architecture
- Production systems
- Experience building:
- Workflow engines
- State machines
- Data-heavy platforms
- Strong understanding of:
- System design
- Distributed systems
- Failure handling
- Experience working in:
- High-scale production environments
- You will build the core backend of an AI platform
- Your work directly impacts:
- Scale
- Reliability
- Product capability
- You will design systems that move from:
- Use-case specific platform-level infrastructure
- Not just API development
- Not limited to feature-level work
- Not disconnected from production realities
- A system architect
- A builder of scalable platforms
- A driver of long-term technical advantage
Can you design backend systems that scale, handle edge cases, and become easier to use as they grow?
