Job Summary

HCLTech AI Labs runs a large and active portfolio of client engagements across global enterprise accounts. At any given time, the team is managing dozens of concurrent initiatives, from proof of concepts and executive workshops to multi-month delivery programmes. Accounts span financial services, pharma, media, manufacturing, and more, with teams distributed across EMEA, APAC, NORAM, and India.

This role owns the Jira-based operating system that keeps all of that visible and manageable. The person we are looking for is not purely a platform administrator. They need to understand how a consulting and engineering organisation like AI Labs actually works, and use that understanding to build Jira structures that reflect reality rather than fight it.

That means knowing the difference between a customer briefing, a hackathon, a proof of concept, and a delivery programme. It means knowing when an epic hierarchy helps and when it is just overhead. And it means being the person architects and team leads turn to when they want to know how to track something properly, not just whether they can.

This role also has a direct responsibility to leadership. Real-time dashboards that give a clear, accurate picture of the portfolio are not a nice-to-have here. They are central to how leadership makes decisions, reports to clients, and spots problems before they become bigger ones. Keeping that data clean, current, and genuinely useful is a core part of the job.

The AI-native dimension of this role is just as important as the Jira expertise. We expect the right person to be using the full range of available AI tools day to day, from conversational assistants and code generation tools to AI-powered analytics, to work faster, produce better outputs, and stay ahead of what the platform can do. People who wait to be shown how to use a new tool are not the right fit here.

Key Responsibilities

What You Will Do Jira Platform Administration Project configuration: Own the setup and ongoing maintenance of Jira projects across the AI Labs engagement portfolio. Design issue hierarchies, workflow states, and transitions that match how the team actually runs its work, not how a textbook says it should. Workflow design: Build and maintain custom workflows, automation rules, and status transitions that reflect the engagement lifecycle from initial opportunity through to delivery and review. Scheme management: Manage permission schemes, notification schemes, issue type schemes, and field configurations. Keep the data clean and access appropriate for a globally distributed team. Boards and roadmaps: Configure and maintain Scrum boards, Kanban boards, and Big Picture roadmaps that give team leads clear sight of their accounts and workstreams without having to ask someone to pull a report. Real-Time Dashboards and Leadership Reporting Leadership dashboards: Design and maintain live dashboards that give the leadership team an accurate, real-time view of the engagement portfolio. These need to be genuinely useful in a senior conversation, not just technically correct. Coverage includes account-level status, pipeline activity, delivery health, and team capacity signals. Proactive reporting: Do not wait to be asked. If something looks wrong in the data, or if a dashboard is no longer reflecting what is actually happening on an account, fix it before anyone notices. Leadership should be able to trust what they see. Stakeholder-ready outputs: Produce regular operational reports covering regional pipeline views and delivery status summaries. Format and structure these for an audience that includes senior architects, regional leads, and executive stakeholders. AI-Native Operations Conversational AI and assistants: Use the current generation of AI assistants, including large language model tools from providers such as Anthropic, OpenAI, and Google, to query Jira data, draft documentation, and accelerate operational tasks. You should already be doing this, not learning to. Code generation tools: Apply AI-powered code and script generation tools, such as those built on models like Codex or equivalent, to automate repetitive Jira administration tasks, build custom integrations, and generate JQL or automation logic faster than writing it from scratch. Atlassian Rovo and platform AI: Use Atlassian Rovo and any native AI features within the Jira and Confluence platform to surface insights, answer operational questions, and reduce the manual overhead of maintaining a large project portfolio. Automation design: Build Jira automation rules, smart values, and integration triggers that connect Jira with Confluence, Microsoft Teams, and other tools in the AI Labs environment. The goal is to remove manual steps, not add them. Engagement Operations Portfolio awarene

Skill Requirements

As Operations Lead, you own the end-to-end Jira operating model for AI Labs. That covers platform strategy, adoption of AI-native tooling, real-time reporting for leadership, and being a trusted advisor to architects and team leads. You are the person who designs the engagement tracking framework and makes sure it scales as the business grows.

This is not a support function. The right person will have a real influence on how AI Labs understands its own portfolio and presents itself to clients. Good operational data makes better decisions possible. Bad operational data means more meetings and less clarity.

Someone proactive. Not someone who flags problems when asked, but someone who spots them before anyone else does and has already started fixing them. If a dashboard is stale, you update it. If a workflow is causing confusion, you redesign it. You do not need a ticket raised to take action.

Someone who is curious about the business, not just the platform. The architects on this team work with banks, pharmaceutical companies, media organisations, and manufacturers. Knowing something about those engagements makes everything you build more useful.

Someone who is genuinely comfortable with AI tools. Not in principle, but in practice. The expectation is that you are already using the current generation of AI assistants, code generation tools, and automation capabilities as part of your daily workflow. That is the baseline here, not the aspiration.

HCLTech AI Labs is the global Centre of Excellence for advanced AI technologies at HCLTech. We work with some of the largest enterprises in the world, providing strategic advice, engineering delivery, and thought leadership on AI adoption and transformation. Our teams span the US, UK, India, and beyond, and the engagements we run are genuinely complex. Keeping that work visible and well-organised matters.

Other Requirements

Required Skills at a Glance The following lists the core skills and minimum experience required for this role. Candidates who do not meet these will not be shortlisted. Skill / Technology                                      Min. Experience    Status Jira Software Administration                          5+ years           Required Jira Workflow and Scheme Configuration                5+ years           Required JQL (Jira Query Language)                             5+ years           Required Jira Dashboards and Custom Reports                    3+ years           Required Jira Automation Rules and Smart Values                3+ years           Required Atlassian Big Picture / Advanced Roadmaps             2+ years           Required Confluence                                            2+ years           Required Atlassian Rovo or equivalent AI platform tooling      1+ years           Required AI Assistants (Claude, ChatGPT, Gemini, Copilot)      1+ years           Required AI Code Generation Tools (Copilot, Codex, or equiv.)  1+ years           Required Experience in consulting / professional services org  3+ y