Senior Software Engineer

Overview
We are looking for a Senior Software Engineer to join our team working on the SaaS platform. This role focuses on designing, prototyping, and building scalable backend services that power next-generation observability and analytics use cases. You will work on cloud-native microservices, solving distributed systems challenges at scale. The team is also responsible for delivering AI capabilities, providing opportunities to work with data-driven approaches and gain exposure to AI/ML concepts and terminology as part of real-world product use cases. This role is well-suited for engineers who enjoy end-to-end ownership, working across evolving technology stacks, and building reliable, high-performance systems in a SaaS environment.

Responsibilities

• Design, prototype, and implement backend microservices for a cloud-based SaaS platform using Go.
• Build and evolve data pipelines and streaming solutions leveraging Kafka and ClickHouse.
• Apply distributed system design principles to deliver scalable, resilient, and performant services.
• Contribute to anomaly detection use cases, collaborating on data-driven and analytical solutions within the observability domain.
• Follow and promote strong engineering practices, including code quality, testing, observability, and operational readiness.
• Work closely with product and cross-functional teams to translate requirements into robust technical solutions.
• Take ownership of features from design through development, testing, and production deployment.
• Continuously learn and adapt to new technologies, including gaining exposure to AI/ML concepts relevant to the problem space.

Qualifications

• Bachelor’s degree in Computer Science, Engineering, or a related field, with 5+ years of industry experience building backend or platform systems (or equivalent practical experience).
• Strong experience developing backend services and APIs using Go in production environments.
• Hands-on experience with distributed systems, including designing services for scale, reliability, and performance.
• Experience working with streaming or messaging systems such as Kafka.
• Familiarity with analytical or OLAP databases such as ClickHouse, or strong experience with similar data stores and a willingness to ramp up quickly.
• Ability to independently design and deliver complex features end-to-end, from requirements through production deployment.
• Solid understanding of cloud-native and microservices architectures in a SaaS environment.
• Experience with observability, monitoring, or performance analysis systems is a strong plus.
• Exposure to anomaly detection, data analytics, or AI/ML concepts is a plus (deep ML expertise not required).
• Comfortable working across teams, contributing to technical discussions, and raising the overall engineering bar through code and design reviews.
• Experience with DevOps practices, CI/CD pipelines, and operating production systems is a plus.