Description :

Role : Lead Backend Engineer Distributed Systems & Big Data

Experience : 4 to 8 Yrs

Location : Remote

Role Overview :

We are hiring a Lead Backend Engineer to build and scale mission-critical backend infrastructure for next-generation AI and Voice platforms. The ideal candidate should have strong hands-on expertise in Go-Lang, distributed event systems, Kubernetes operations, and large-scale data platforms.

This is a high-ownership role requiring someone who has worked extensively on production-grade, high-availability systems handling massive data and transaction volumes.

What You Will Own :

- Backend orchestration services and core platform development in Go-Lang.

- Real-time streaming and event-driven architectures using Kafka or Pulsar.

- Messaging reliability including partitioning, replay handling, ordering guarantees, and dead-letter strategies.

- Big data platforms for transcripts, analytics, telemetry, and OpenSearch workloads.

- Kubernetes-based production environments including autoscaling, performance tuning, and stateful services.

- Reliability engineering including observability, monitoring, SLOs, and production incident management.

- Technical leadership across backend architecture, engineering standards, and mentoring.

Required Skills :

- Strong production experience in Go-Lang as the primary programming language.

- Hands-on expertise managing Kafka or Pulsar clusters and large-scale event pipelines.

- Strong operational knowledge of Kubernetes with experience debugging live production issues.

- Experience with at least one major big data or analytics technology such as ClickHouse, Spark, DuckDB, BigQuery, or lakehouse architectures.

- Good understanding of gRPC, Protocol Buffers, and schema/version management.

- Experience designing scalable, fault-tolerant distributed systems.

Leadership & Ownership :

- Ability to independently drive backend initiatives end-to-end.

- Strong problem-solving and production troubleshooting capabilities.

- Experience mentoring engineers and guiding technical direction.

- Effective collaboration across globally distributed teams and time zones.

Preferred :

- Exposure to AI/ML or Voice technology platforms.

- Experience with observability stacks, telemetry systems, and infrastructure optimization.

- Prior experience in high-scale SaaS or real-time platforms