Job Description

Software development: Write, test, and maintain Python scripts, utilities, and small application components. Jira workflows: Help maintain project boards, issue types, fields, workflows, dashboards, and automation rules within approved permissions and change procedures. Confluence documentation: Create and update technical documentation, knowledge articles, release notes, troubleshooting guides, and reusable page templates. Integrations: Assist with REST API and webhook integrations between Jira, Confluence, databases, and internal applications. Application support: Triage tickets, reproduce reported problems, review logs, perform approved diagnostic database queries, and escalate complex issues with supporting evidence. Workflow automation: Help automate repetitive support and operational tasks using Python and a team-approved orchestration or automation tool. AI-enabled features: Assist with simple ML or LLM integrations, such as ticket categorization, summarization, or knowledge retrieval, with appropriate validation and human review. Controlled delivery: Participate in code reviews, testing, and supervised releases; keep users informed of ticket progress and document resolutions. Responsible AI-assisted development: Use approved coding assistants to draft or explain code, then review and test the output before proposing changes. Requirements E xperience and education: 0–2 years of relevant experience; a degree in computer science, engineering, information systems, or a related field, or equivalent practical experience. Python: Basic programming skills covering functions, data structures, scripting, exception handling, and debugging. Databases: Understanding of tables, relationships, keys, and basic SQL queries, including joins; awareness of access controls and safe database operations. Jira: Familiarity with issues, boards, workflows, priorities, filters, and basic Jira Query Language (JQL). Prior enterprise administration experience is not required. Confluence: Ability to create and organize pages, use templates, and maintain readable technical and support documentation. ML and LLM fundamentals: Basic understanding of what ML models and LLMs do, their limitations, and why their outputs require validation. Orchestration: Awareness of triggers, actions, dependencies, retries, and logging; introductory exposure to Jira Automation, n8n, Airflow, or an equivalent tool. Development tools: Basic Git, HTTP/REST APIs, JSON, testing, and responsible use of AI-assisted coding tools. Application support: A methodical troubleshooting approach, clear ticket updates, attention to detail, and willingness to follow escalation procedures. Preferred qualifications: Relevant projects: Experience building a small application, integration, automation script, or support utility. Atlassian exposure: Familiarity with Jira or Confluence APIs, Jira Service Management, permission concepts, or sandbox configuration. Broader development skills: Exposure to JavaScript, HTML/CSS, Linux commands, or CI/CD concepts. Support practices: Awareness of incident, problem, and change-management practices, including keeping accurate resolution records.