Lead Backend Engineer

Position: Backend Engineer / Lead Backend Engineer

Location: Bangalore (Hybrid)

Experience: 6+ Years

• Backend Engineer: 5+ years of hands-on experience designing, developing, deploying, and maintaining production-grade backend services at scale.
• Lead Backend Engineer: 10+ years of software engineering experience, with demonstrated ownership of backend architecture, technical leadership, and development of highly scalable and reliable systems.
• Strong experience working on distributed, high-availability backend systems in production environments.

Core Technical Skills

Python & Backend Development

• Expert-level proficiency in Python for server-side application development.
• Strong understanding of object-oriented and functional programming concepts, clean code principles, design patterns, and writing maintainable, testable production code.
• Hands-on experience with at least one modern Python web or asynchronous framework such as FastAPI, aiohttp, Flask, or equivalent.
• Strong understanding of WSGI and ASGI application models and their implications for synchronous and asynchronous workloads.
• Experience developing scalable, modular backend services and integrating them with internal and external systems.

Service & API Design

• Strong experience designing and implementing production-grade REST APIs and/or gRPC services.
• Understanding of different API communication patterns, including:
• Request/response APIs
• Streaming and asynchronous communication
• Pagination and filtering
• API versioning
• Idempotency and safe retry mechanisms
• Authentication and authorization
• Ability to design clear, consistent, and backward-compatible API contracts.
• Experience evolving APIs and services without disrupting existing consumers or dependent systems.
• Strong understanding of API performance, scalability, security, and reliability considerations.

Database & Data Layer

• Strong proficiency in SQL, relational database concepts, and data modeling.
• Experience designing efficient schemas and optimizing complex queries.
• Strong understanding of:
• Database indexing and query optimization
• Transactions and transaction isolation
• Connection pooling
• Concurrency and consistency
• Data integrity and schema evolution
• Hands-on experience working with multiple types of data stores, including:
• Relational databases
• Cloud data warehouses such as Snowflake
• NoSQL/key-value databases such as DynamoDB
• Ability to select appropriate storage technologies based on scalability, consistency, latency, and workload requirements.

Backend Architecture & Distributed Systems

• Strong understanding of common server-side and distributed-system design patterns.
• Experience implementing caching strategies to improve application performance and reduce database load.
• Hands-on experience with background jobs, workers, queues, and asynchronous processing.
• Experience designing and implementing event-driven architectures and processing systems.
• Strong understanding of:
• Rate limiting and throttling
• Retries and exponential backoff
• Request and service timeouts
• Circuit-breaking and failure-handling patterns
• Message processing and delivery guarantees
• Ability to identify bottlenecks and design systems that remain reliable under increasing load.

Performance & Reliability

• Strong experience troubleshooting and optimizing backend application performance.
• Experience with profiling, benchmarking, load testing, and performance analysis.
• Ability to evaluate and balance latency, throughput, resource utilization, and scalability.
• Experience designing systems for high availability and resilience.
• Strong understanding of graceful degradation and failure-handling strategies.
• Ability to anticipate failure scenarios and design services that remain stable when dependencies, infrastructure, or individual components fail.
• Experience diagnosing and resolving performance and reliability issues in live production environments.

Observability & Production Operations

• Strong experience implementing and using modern observability practices, including:
• Structured logging
• Application and infrastructure metrics
• Distributed tracing
• Monitoring and alerting
• Ability to use observability data to identify root causes of production issues.
• Experience debugging complex issues across distributed services and dependencies.
• Comfortable investigating and resolving live production incidents, performance degradation, service failures, and unexpected application behavior.
• Strong understanding of production readiness, monitoring, alerting, incident response, and operational best practices.