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Our client in Irvine, CA is looking for a Solutions Architect. This is a contract position.

What You Will Do:

We are seeking a highly skilled and experienced AI Solution Engineer with a specialized focus on building and deploying AI agents within our ROVO platform, coupled with extensive expertise in Atlassian Administration. In this critical role, you will be instrumental in designing, developing, and optimizing AI agents that streamline operations, enhance user experiences, and provide intelligent automation across our enterprise systems. Your deep knowledge of Atlassian products will be essential for managing and optimizing our development and collaboration toolchain, ensuring seamless integration and efficient workflows for our AI initiatives.

Key Responsibilities

• AI Agent Development:

Design, develop, test, and deploy robust and scalable AI agents and solutions primarily within the ROVO platform.

Collaborate with product managers, data scientists, and other engineers to translate business requirements into technical specifications for AI agent functionality.

Implement natural language processing (NLP), machine learning (ML) models, and other AI techniques to enhance agent intelligence and performance.

Monitor, debug, and optimize AI agent performance, ensuring high availability and accuracy.

Stay current with the latest advancements in AI, machine learning, and agent technologies, particularly those relevant to ROVO.

• Atlassian Administration & Integration:

Serve as a primary administrator and subject matter expert for our Atlassian suite, including Jira Software, Confluence, Bitbucket, Jira Service Management, and associated plugins/integrations.

Configure, maintain, and troubleshoot Atlassian applications, ensuring optimal performance, security, and user experience.

Develop and implement custom workflows, schemes, screens, and permissions within Jira to support various project methodologies (Agile, Scrum, Kanban) and AI development cycles.

Manage user access, groups, and permissions across all Atlassian products.

Integrate Atlassian tools with other internal systems (e.g., CI/CD pipelines, monitoring tools) to create cohesive and automated development environments for AI projects.

Provide expert support and training to teams on best practices for using Atlassian tools to manage AI development and operations.

Plan and execute upgrades, migrations, and instance consolidations for Atlassian products.

• Solution Engineering & Support:

Act as a bridge between technical teams and business stakeholders, articulating complex AI concepts and Atlassian capabilities clearly.

Provide technical guidance and support for the adoption and effective use of AI solutions and Atlassian tools.

Contribute to documentation, best practices, and knowledge sharing within the engineering team.

Identify opportunities for process improvement and automation using AI and Atlassian capabilities.

What You Will Need:

Basics:

• Bachelor's degree in Computer Science, Artificial Intelligence, Software Engineering, or a related technical field, or equivalent practical experience.
• 3+ years of experience in developing, deploying, and maintaining AI agents, chatbots, or intelligent automation solutions.
• Proven hands-on experience building AI agents in the ROVO platform (or similar proprietary/enterprise AI agent development platforms).
• 5+ years of demonstrable experience as an Atlassian Administrator, with in-depth knowledge of Jira Software, Confluence, and Bitbucket.
• Experience with REST APIs and integrating different software systems.
• Solid understanding of database concepts (SQL/NoSQL) and data integration.
• Excellent problem-solving skills, with an ability to diagnose and resolve complex technical issues.
• Strong communication and interpersonal skills, capable of working effectively with diverse teams and stakeholders.
• Salary range: 93k - 127k annual.

Preferred:

• Master's degree in AI, ML, or a related field.
• Certifications in Atlassian products (e.g., Jira Administrator, Confluence Administrator).
• Experience with cloud platforms (AWS, Azure, GCP) and MLOps practices.
• Familiarity with containerization technologies (Docker, Kubernetes).
• Experience with other AI frameworks, libraries (e.g., TensorFlow, PyTorch), or agent development tools.
• Knowledge of agile methodologies and DevOps practices.