Jira Consultant

Jira Consultant (Contractor) with focus on AI-driven Product Lifecycle Automation

About the Company

ZAGENO offers the largest life sciences lab supply marketplace. Our one-stop shop helps scientists, lab managers, and procurement leaders compare products, source alternatives, track deliveries, and communicate order statuses in real time, accelerating innovation by saving valuable time. Leveraging advanced AI, ZAGENO enhances supply chain resilience and makes the customer experience superior, seamlessly integrating with existing systems to boost productivity and make online shopping for research materials convenient, efficient, and reliable. We are committed to innovation, excellence, and fostering a supportive, and dynamic work environment. 

About the Role 

The Jira Consultant will lead the configuration, customization, and rollout of Jira workflows and boards that reflect our end-to-end product delivery process, involving Product, Engineering, QA, DevOps, Data Engineering, and Analytics teams. We are looking for a consultant who not only understands how to structure Jira for cross-functional teams, but who can also identify opportunities to introduce AI and Large Language Model (LLM)-powered automations into the product lifecycle to reduce manual overhead and improve execution speed.

This is a hands-on implementation role requiring deep Jira expertise, excellent communication skills, and a strong understanding of Agile/Scrum methodologies and cross-functional workflows.

In this role you will:

• Configure and optimize Jira Cloud for ZAGENO’s Product Development Lifecycle, based on pre-defined workflows


• Create and manage:
  
  
  
  • Master Board 
  
  
  • Team Boards for Development, QA, DevOps, Data Engineering, and Analytics
  
  
  
  


• Build custom workflows for issue types:
  
  
  
  • Epic, Story, Bug, Task, Spike, Sub-task
  
  
  
  


• Define and implement:
  
  
  
  • Issue statuses, transitions, conditions, validators, post-functions
  
  
  • Automation rules (e.g., cross-board status sync, comment triggers, alerts)
  
  
  • Issue templates, screen schemes, and permission schemes
  
  
  
  


• Leverage LLM-based automation where possible to generate summaries, auto-fill issue descriptions, identify blockers via natural language, and assist with sprint planning using AI insights


• Evaluate AI-native integrations for Jira (e.g., Atlassian Intelligence, GPT plug-ins, third-party apps) and recommend how they can reduce manual effort


• Set up issue linking, hierarchy, and standard labels across all boards


• Design and roll out Jira dashboards and reporting for sprint velocity, QA pass/fail rate, release readiness, and data validation status


• Work with stakeholders to gather requirements and fine-tune workflows


• Train internal teams on new Jira processes and best practices


• Document all workflows, board configurations, Jira Consultant (Contractor) with focus on AI-driven Product Lifecycle Automation, and automation in Confluence
  
  

About you:

• 5+ years of experience configuring and administrating Jira Cloud for Agile/DevOps organizations


• Strong understanding of Jira issue types, workflows, automation rules, permissions, and advanced JQL


• Experience implementing Jira across cross-functional Agile teams


• Prior experience working with:
  
  
  
  • Product lifecycle workflows
  
  
  • QA/DevOps/Data integration into issue tracking
  
  
  
  


• Familiarity with or hands-on experience in integrating AI/LLM tools into operational workflows (e.g., OpenAI, Atlassian Intelligence, GitHub Copilot, custom GPT workflows)


• Proficiency with Jira Automation, Advanced Roadmaps, and integration tools (e.g., Confluence, Slack, GitHub)


• Excellent communication skills and stakeholder management


• Strong documentation and training capability


• Jira Certified (preferred)

What You’ll Deliver

• A fully configured Jira workspace reflecting ZAGENO’s Product Development Lifecycle


• Linked and automated workflows across 6+ functional boards


• Dashboards and reporting tied to product, QA, and data KPIs


• Recommendations and initial prototypes of LLM-powered automation within Jira (e.g., auto-ticket generation from slack, AI-suggested backlog grooming, smart summaries)


• Onboarding guides and Confluence documentation for internal use