VuNet Systems - Senior Engineer/Lead - AI Powered Observability Platform

Description :

ROLE : Senior Engineer/Lead - Scale & Performance AI-Powered Observability Platform

LOCATION : Bangalore (Onsite)

EXPERIENCE : 612 years

FUNCTION : Engineering Platform / DevOps / SRE

About the Role :

- Design and execute load, stress, soak, and capacity tests for microservices, agents, and ingestion layers.

- Identify performance bottlenecks across infrastructure (CPU/memory/IO) and application layers (API latency, throughput, GC behavior, etc.).

- Develop and maintain performance test frameworks and benchmarking environments (preferably Kubernetes-based).

- Partner with DevOps and SRE teams to tune system configurations (Kubernetes, Postgres/TimescaleDB, ClickHouse, Kafka, etc.) for scale.

- Instrument services with OpenTelemetry metrics and traces to measure system health and latency distribution (p50/p95/p99).

- Contribute to capacity planning, horizontal/vertical scaling strategy, and resource optimization.

- Analyze production incidents for scale-related root causes and drive permanent fixes.

- Collaborate with engineering teams to design scalable architecture patterns and define SLIs/SLOs for system performance.

- Document performance baselines, tuning guides, and scalability best practices.

Skills & Qualifications :

- Strong background in performance engineering for large-scale distributed systems or SaaS platforms.

- Expertise in Kubernetes, container runtime (container/Docker), and resource profiling in containerized environments.

- Solid knowledge of Linux internals, CPU/memory profiling, and network stack tuning.

- Hands-on experience with observability tools Prometheus, Grafana, OpenTelemetry, Jaeger, Loki, Tempo, etc.

- Familiarity with datastores used in observability platforms e.g., ClickHouse, PostgreSQL/TimescaleDB, Elasticsearch, or Cassandra.

- Experience building and executing performance benchmarking frameworks using tools like k6, Locust, JMeter, or custom Golang/Python scripts.

- Ability to interpret metrics (CPU usage, memory, GC, latency) and correlate across systems.

- Strong analytical and problem-solving skills with an automation-first mindset.

Good-to-Have :

- Experience with agent benchmarking (OpenTelemetry Collector, custom data shippers).

- Exposure to streaming systems like Kafka, NATS, or Pulsar.

- Experience with CI/CD pipelines for performance testing and regression tracking.

- Understanding of cost optimization and capacity forecasting in cloud environments (AWS/GCP/Azure).

- Proficiency in Go, Python, or Bash scripting for automation and data analysis.