IBM Recruitment 2026

IBM

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1 day ago

Key Responsibilities

As a Software Engineer in the Confluent division, you will collaborate with seasoned developers on well-defined software features:
Feature Delivery: Implementing and executing well-scoped tasks and product updates on time, under the guidance of senior mentors.
Cluster & Console Enhancements: Contributing to hybrid-first management capabilities (USM Agent, Cloud Console) or improving cluster health, topic visibility, consumer monitoring, and data connector visibility (C3 workflows).
System Design: Drafting brief architectural design documentation for your own software tasks and integrating structural review feedback from peers.
Quality Assurance: Writing functional unit tests, fixing code defects, and reviewing team code to foster a robust engineering culture.
Production Troubleshooting: Investigating real-time production and customer issues by parsing distributed system logs and reading telemetry metrics with team support.
On-Call Rotations: Participating in supportive on-call rotations to learn how to debug, escalate, and mitigate complex outages in staging and production environments.

IBM is evaluating engineering applicants who possess a solid logical core, clear backend fundamentals, and a strong willingness to learn complex distributed networks:
Core Education: Bachelor’s or Master’s Degree in Computer Science, Engineering, or equivalent practical industry experience.
Programming Languages: Ability to write clean, maintainable, and robustly tested backend code in at least one modern language. Highly prefer candidates with expertise in **Java or Go**.
CS Fundamentals: Solid grasp of foundational computer science principles, including data structures, sorting algorithms, concurrency, networking protocols, and operating systems.
System Curiosity: High level of curiosity regarding the inner workings of distributed storage systems and how large-scale services like Apache Kafka are built and operated.
Collaboration Mindset: Strong written and verbal communication skills, a self-starter attitude, and ease with asking technical questions and seeking constructive feedback during peer code reviews.
Relevant coursework, internships, or personal projects involving Apache Kafka, cloud infrastructure, or distributed storage systems.
Basic exposure to modern container orchestration tools such as Kubernetes, Docker, or major cloud platforms (AWS, GCP, or Azure).
Active contributions to open-source software libraries.
A keen interest in platform engineering, system observability, and monitoring frameworks.

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