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Job Summary:
The Systems Engineer will provide senior-level technical leadership for enterprise Kafka platform engineering, distributed systems, automation, DevOps, and AI-driven engineering initiatives. The role will design and support secure, highly available Kafka architectures across on-premises and cloud environments, while driving automation, operational efficiency, and enterprise integration. The ideal candidate will have extensive hands-on experience with Confluent Kafka Platform, strong Linux, networking, security, and enterprise platform engineering expertise, and recent practical experience leveraging AI-powered development tools and building AI-driven agents and workflows to improve engineering and operational productivity.

Key Responsibilities
• Design and implement secure Kafka architectures, including authentication, authorization, encryption, and network isolation.
• Define and support high availability, disaster recovery, and data replication strategies for Kafka platforms.
• Ensure Kafka platform implementations align with enterprise security, compliance, and governance standards.
• Advise on data ingestion, event streaming, batch processing, and stream processing architectures.
• Provide guidance on data modeling and serialization standards, including Avro, Protobuf, and JSON Schema.
• Support enterprise integration use cases and resolve complex Kafka-related integration challenges.
• Design and build AI agents, custom skills, and related frameworks to automate engineering and operational workflows at scale.
• Leverage AI-powered tools, including GitHub Copilot and AI agents, to accelerate development, automate testing, improve code quality, and enable intelligent SDLC workflows.
• Design agentic workflows and multi-agent orchestration patterns to address complex distributed systems, integration, and operational challenges.
• Apply advanced prompt engineering and AI-assisted development techniques to improve engineering productivity and efficiency.
• Drive automation-first operations using Python, Ansible, and scripting.
• Build and maintain self-service operational tools to reduce day-to-day support overhead.
• Integrate Kafka platform operations with DevOps and CI/CD tooling such as Azure, Jenkins, Puppet, and Chef.
• Lead deep-dive investigations into complex production issues and outages.
• Perform root cause analysis, document findings, and drive remediation through closure.
• Operate effectively during high-pressure outages and incident management situations.
• Act as a trusted technical advisor to engineering, operations, and leadership teams.
• Communicate complex technical concepts clearly to technical and non-technical stakeholders.
• Collaborate effectively with cross-functional teams and vendors while maintaining strong customer focus and ownership.

Required Qualifications
• 10+ years of experience in distributed systems, messaging, and enterprise platform engineering.
• Extensive hands-on experience with Confluent Kafka Platform across both on-premises and cloud environments.
• Strong background in Linux/Unix environments, networking, operating system performance, and security.
• Proven experience with automation, DevOps, and operational tooling.
• Recent hands-on experience leveraging AI-powered tools to accelerate software development and improve engineering productivity.
• Experience with GitHub Copilot or comparable AI-assisted development tools, including prompt engineering and workflow integration.
• Experience building or implementing AI-driven agents, agentic workflows, or multi-agent automation solutions.
• Strong understanding of Kafka security, authentication, authorization, encryption, high availability, disaster recovery, and replication.
• Strong understanding of event streaming, data integration, and enterprise messaging architectures.
• Excellent written and verbal communication skills.
• Strong organizational, relationship management, collaboration, and teamwork skills.

Preferred Qualifications
• Confluent Kafka and/or relevant cloud certifications.
• Experience supporting large-scale, regulated enterprise environments.