Senior Software Engineer - IT - United States

ACCOUNTABILITIES:
Designs, codes, tests, debugs and documents software according to systems quality standards, policies and procedures. Analyzes business needs and creates software solutions. Responsible for preparing design documentation. Prepares test data for unit, string and parallel testing. Evaluates and recommends software and hardware solutions to meet user needs. Resolves customer issues with software solutions and responds to suggestions for improvements and enhancements. Works with business and development teams to clarify requirements to ensure testability. Drafts, revises, and maintains test plans, test cases, and automated test scripts. Executes test procedures according to software requirements specifications Logs defects and makes recommendations to address defects. Retests software corrections to ensure problems are resolved. Documents evolution of testing procedures for future replication. May conduct performance and scalability testing.

RESPONSIBILITIES:
Leads small to moderate budget projects; may perform in project leadership role and/or may supervise the activities of lower level personnel. Provides resolutions to a diverse range of complex problems. Executes schedules, costs and documentation to ensure assigned projects come to successful conclusion. May assist in training, assigning and checking the work of less experienced developers. Performs estimation efforts on projects and tracks progress. Drafts and revises test plans and scripts with consideration to end-to-end system flows. Executes test scripts according to application requirements documentation. Logs defects, identifies course of action and performs preliminary root cause analysis. Analyzes and communicates test results to project team.

The Messaging and Streaming Platform Engineer provides middleware messaging engineering, administration and system support for new and existing production RabbitMQ and Kafka environments, including performance of the following tasks:

Software installation, patch installation, upgrades, object definition, configuration, security, system monitoring and tuning, disaster recovery planning, automation implementation and backup and recovery.

Work independently on day-to-day monitoring and operations of cloud and legacy applications. You will be required to develop automation using AI-assisted engineering practices. Identify opportunities to leverage AI and intelligent automation to reduce manual operational effort and accelerate service delivery.

You will:
Design, build and support enterprise large-scale distributed Messaging platforms, including software installation, patch installation, upgrading software, disaster, recovery planning, backup and recovery.
Leverage AI-powered development and operational tools to accelerate troubleshooting, documentation, automation, and incident resolution.

Identify and implement best practices to support a highly available platform
Implement and enforce security practices for enterprise messaging platforms
Provide Operational support for platform issues to application development teams
Address performance and scalability challenges posed by new or changing Kafka producers and consumers.
Work in an agile global team setting

Essential Requirements
6 to 12 years of experience in middleware Kafka messaging, application platforms management and distributed architecture/solutions
Strong proven experience in managing RabbitMQ and Kafka for large-scale enterprise distributed systems
Experience with monitoring and logging tools such as Grafana, Prometheus, Splunk, Dynatrace
Deep and extensive knowledge in configuration, troubleshooting, optimization of Kafka / RabbitMQ
Proficiency with Python, shell scripts, & configuration management tools, preferably Ansible
Practical experience using AI-powered development and engineering tools and solutions to improve development and operational productivity.

Desirable Requirements
Experience in applying Generative AI /Agentic AI to infrastructure operations, platform engineering, or software development workflows.
Familiarity with AI-assisted observability, incident management, operational analytics, or intelligent automation solutions.
Proven expertise in Kubernetes Container Orchestration and Docker Containers.
Experience in messaging / streaming platforms like IBM MQ, Active MQ, Apache Flink etc.