Knowledge Management PM

Celonis; Bengaluru; On-site; INR 1,200,000 - 1,800,000; Full time

Job summary

Celonis is looking for a Knowledge Management PM/Analyst in Bengaluru, India. This pivotal role bridges traditional knowledge management with AI-driven productivity. You will manage projects, engage cross-functional teams, and optimize knowledge assets for AI applications.

Ideal candidates have 4-6 years of experience in Knowledge Management, strong AI tool expertise, and skills in prompt engineering. Join Celonis and help us transform processes for our customers and the planet.

Qualifications

• Minimum of 4–6 years of professional experience in Knowledge Management or Data Analysis.
• Hands-on experience with AI tools, focusing on Knowledge Optimisation.
• Ability to craft and refine prompts for AI models.

Responsibilities

• Support design of AI-ready KM strategies to ensure optimized knowledge capture.
• Apply prompt engineering techniques to enhance knowledge retrieval.
• Assist in implementing a Global Knowledge Governance Model.

Skills

Knowledge Management

Data Analysis

AI Tools

Prompt Engineering

Tools

Confluence

AI Models

Job description

Celonis is the global leader in Process Intelligence and the pioneer of Process Mining technology. As one of the world’s fastest-growing enterprise SaaS companies, we are changemakers pushing the boundaries of what’s possible. We invest heavily in advanced AI capabilities—specifically our Process Intelligence Graph—to turn data insights into immediate business action. We believe there is a massive opportunity to unlock global productivity and sustainability by placing intelligence at the core of every business process. Join our mission to make processes work for people, companies, and the planet.

The Team

The Knowledge Management (KM) team is a global function dedicated to building a robust internal knowledge ecosystem. The team treats internal knowledge assets as the core fuel for enterprise AI productivity, bridging the gap between traditional knowledge architecture and automated discovery to drive high-impact efficiency across the organization.

The Role

The Knowledge Management PM / Analyst acts as a critical bridge between traditional knowledge management and the future of AI-driven productivity. Supporting the Global Head of KM, you will manage end-to-end projects, engage cross-functional stakeholders, and ensure company knowledge assets are structured, governed, and optimized for Large Language Models (LLMs). This is a high-impact role designed for an expert who understands that great AI relies entirely on solid KM principles.

The work you’ll do

• KM Strategy & AI Integration: Support the design and implementation of AI-ready KM strategies, ensuring knowledge is captured and formatted for optimized discovery.
• Prompt Engineering: Apply advanced prompt engineering techniques to internal AI tools to improve the relevance and accuracy of automated knowledge retrieval.
• Global Governance: Assist the Head of KM in implementing a Global Knowledge Governance Model addressing AI ethics, data privacy, and the validation of AI-generated content.
• Metadata & Tagging Management: Execute standardized processes for knowledge tagging and storage, ensuring metadata schemas support advanced AI search capabilities.
• Cross-Functional Collaboration: Represent the KM function across departments, advocating for a "Knowledge First" approach to AI and partnering with Enablement and L&D to train the workforce.
• Project Management: Manage end-to-end KM projects within the fast-paced timelines required by active corporate AI rollouts.
• Repository Optimization: Audit and optimize repository platforms like Confluence to remove "noise" and ensure AI models train on high-quality, current data.
• Performance Monitoring: Analyze usage metrics, user feedback, and ecosystem health to prevent information decay and refine prompt libraries.

The qualifications you need

• Experience: Minimum of 4–6 years of professional experience in Knowledge Management, Operations, or Data Analysis, with a heavy emphasis on Knowledge Optimisation.
• AI Expertise: Hands‑on experience with AI tools and a deep understanding of how KM principles (taxonomies, and metadata) power AI discovery.
• Prompt Engineering: Proven ability to craft and refine prompts to extract high-quality, structured information from AI models.