Senior Software Engineer — Distributed Systems (Rust)

VuNet Systems

Greater Bengaluru Area

Role: Senior Software Engineer — Distributed Systems (Rust)

Experience: 5 - 8 Years

Education: B.Tech/Master's

Location: Bengaluru (Work from office)

Join Our Journey at VuNet

VuNet is a pioneer in Business Journey Observability, leveraging Big Data and Machine Learning to transform digital experiences across the financial services. Our deep-tech platform provides end-to-end visibility into customer journeys — empowering proactive issue resolution, operational resilience, and superior user satisfaction.

If you’ve ever used instant payment systems like UPI, chances are you’ve already experienced the power of our platform — we monitor over 28 billion digital transactions monthly (that’s equal to watching 3 years of tik-tok videos), touching 300 million users with leading banks and financial institutions.

VuNet is Series B funded, part of NASSCOM DeepTech Club, awarded NASSCOM’s AI Gamechanger, recognized in Forbes DGEMS 200 and by several global analysts including Gartner, Omdia.

We’re building a new category of observability purpose-built for complex digital journeys — across payments, lending, core banking and more — already powering some of the largest banks in India and MEA.

Your Role: Senior Software Engineer — Distributed Systems (Rust)

We are building the database and cold-storage tier for observability data at petabyte scale, with a focus on making telemetry data cost-efficient to store and fast to query.

Our technology stack is centered around Rust and Apache DataFusion, and we are looking for a Senior Software Engineer who enjoys solving hard problems across distributed systems, database engines, query execution, and storage.

You will have the opportunity to shape the architecture of a critical data platform from the ground up and work on systems that ingest and query logs, metrics, and traces.

Roles & Responsibilities

Design and build scalable and reliable systems for storing and querying observability data.
Build database and storage components using Rust and Apache DataFusion.
Work across the query engine and storage layers, including query planning, execution, optimization, and data access.
Design distributed systems for high throughput, low latency, fault tolerance, and horizontal scalability.
Work with columnar and analytical data formats such as Apache Arrow and Parquet.
Optimize query performance across CPU, memory, I/O, and network boundaries.
Design systems for efficient cold-tier storage, balancing storage cost, query performance, and data retention requirements.
Build production-grade systems with strong observability, reliability, and operational characteristics.
Participate in architecture and design reviews and make pragmatic technology trade-offs.

What we are looking for

5+ years of software engineering experience, with significant time spent on backend or infrastructure systems.
At least 3 years of hands-on Rust programming, including production systems you have shipped and operated. This is a hard requirement.
Strong understanding of distributed systems and database fundamentals.
Hands-on experience with one or more of: Query engines, Databases, Distributed storage, Data processing systems, Search/indexing systems, Analytics platforms
Strong understanding of concurrency, parallelism, memory management, and networking.
Strong understanding of data structures, algorithms, and system design.
Experience with Kubernetes — deploying, operating, and debugging stateful workloads in production.
Strong debugging and performance-profiling skills.
Experience taking systems from design through to reliable operation at scale.

Good to Have

Experience with Apache DataFusion or other query engines such as Spark, Trino, DuckDB, ClickHouse, or Velox.
Experience contributing to or working with open-source database/query-engine projects.
Experience with Go.
Experience with observability systems and telemetry data, particularly logs, metrics, and traces.
Experience with time-series or analytical databases.
Familiarity with Apache Arrow, Parquet, Delta Lake, or Iceberg.
Experience with cloud object storage such as S3, GCS, or Azure Blob Storage, including compaction, indexing, and tiered storage over object stores.
Experience with cloud-native infrastructure beyond Kubernetes itself — operators, service meshes, and cloud-native storage and networking.

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