Senior Software Engineer — Distributed Systems

About the role:

Conviva helps businesses understand and improve experiences across video, digital applications, and AI agents. Our engineering teams build distributed systems that turn streaming data into real-time insights. You will design and build high-scale distributed systems, with a focus on Microservices (Rust,Python, Scala), Stateful Stream Processing, Analytical Databases and analytics AI Agents. You will own components from design through production, solving challenges in high throughput ingestion, event processing, distributed state management, storage, and query performance. The role requires understanding system internals, making sound engineering trade-offs, and building services that remain reliable under load and failures.

What Success Will Look Like:

• Build Rust-based microservices for high-throughput, low-latency data processing and analytics.
• Design service APIs and communication patterns with effective backpressure and failure handling.
• Develop streaming pipelines for ingestion, sessionization, aggregations, and stateful computations.
• Improve analytical storage and query performance through data modeling, indexing, and execution strategies.
• Investigate bottlenecks across CPU, memory, disk, and network; improve performance and infrastructure efficiency.
• Contribute to design reviews, mentor engineers, and collaborate across global teams.

Who You Are & What You've Done:

• 4–6 years of software engineering experience, including ownership of production backend.
• Strong programming skills in Rust, Python, Scala, Java, or Go.
• Strong fundamentals in data structures, algorithms, concurrency, networking, and operating systems.
• Experience building distributed systems, streaming platforms, databases, or high-scale microservices.
• Ability to reason about correctness and performance, diagnose failures, and explain design trade-offs.

Experience that would be valuable:

• Production Rust development, including asynchronous programming and concurrency.
• Kafka, Flink, Spark, or similar systems, especially event-time processing, state management, and recovery.
• ClickHouse, Druid, or other analytical databases, including storage layouts and query optimization.

Why this role

Own core infrastructure, influence architectural decisions, and solve distributed systems problems behind real-time analytics at scale. You do not need every technology listed. We value strong systems fundamentals, technical depth, and the ability to learn.