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Platform Product Owner-AI Enablement & Vendor Experience

Maersk


Job Location:

Mumbai - India

Monthly Salary: Not provided by the employer
Posted: 21 July 2026 (30+ days ago)
Application Deadline: 18 November 2026
Vacancies: 1 Vacancy

Job Summary

Develops AI Automation and Agents for ASSP

About Us:

Maersk is a global leader in integrated logistics and have been industry pioneers for over a century. Through innovation and transformation we are redefining the boundaries of possibility continuously setting new standards for efficiency sustainability and excellence.

At Maersk we believe in the power of diversity collaboration and continuous learning and we work hard to ensure that the people in our organization reflect and understand the customers we exist to serve.

With over 100000 employees across 130 countries we work together to shape the future of global trade and logistics.

Join us as we harness cutting-edge technologies and unlock opportunities on a global scale. Together lets sail towards a brighter more sustainable future with Maersk.

Role Purpose:

As Platform Product Owner-AI Enablement you will drive the delivery of agentic AI across the platform from identifying use cases and ensuring data foundations are in place through to building launching and tracking the value they create. You will translate process pain points into well-scoped AI opportunities ensure data is catalogued and production-ready before any agent is built and coordinate with enterprise architects and engineering managers to bring agents into production. You will use tools such as Claude Code Microsoft Copilot and modern AI orchestration frameworks to prototype and build AI agents directly operating as a hands-on builder not only a specification writer.

Core Accountabilities:
1. AI Use Case Development & Pipeline

Partner with use case owners and Global Process Leads to identify qualify and size AI opportunities across enterprise workflows.

Maintain a sequenced AI use case pipeline aligned to the AI Transformation roadmap and OP priorities.

2. Data & Catalogue Enablement

Define data requirements (sources fields quality thresholds) needed for each agent to function reliably and own Data Catalogue entries as a mandatory gate before POC or build.

Build and maintain semantic search and retrieval layers (vector databases embedding pipelines) to support agent grounding.

3. Technical Delivery & Hands-On AI Development

Co-own technical design of AI agents with architects and engineering managers; define APIs data flows and integration patterns.

Design and build RAG pipelines multi-agent workflows and orchestration logic using frameworks such as LangChain LangGraph LlamaIndex or AutoGen.

Fine-tune prompts and evaluate outputs across LLMs (GPT Claude Gemini or open-source models) for business scenarios.

Deploy AI solutions on cloud platforms (Azure AWS or GCP) applying responsible AI and governance practices throughout.

4. Adoption & Value Tracking

Own business readiness for each launch (stakeholder alignment training communication) and mitigate adoption risks early.

Define and track business KPIs (e.g. hours saved error reduction) and technical KPIs (e.g. accuracy latency) per agent reporting value realisation to the Head of AI Enablement.

Skills & Experience Required:

Experience in product ownership business analysis or process improvement within a procurement supply chain or operations environment.

Demonstrable hands-on daily use of AI tools (Claude Copilot ChatGPT or equivalent) to solve real work problems.

Working proficiency in Python and SQL sufficient to prototype and iterate on agent code not just specify it.

Comfortable reading datasets writing basic SQL and assessing quality without needing to be a data engineer.

Preferred:

Deeper agentic AI experience (multi-agent systems tool use prompt engineering) with at least a working prototype built.

Experience with Databricks Snowflake Spark or similar data platforms and deploying AI workloads on major cloud providers.

Hands-on experience with at least one AI orchestration framework (LangChain LangGraph LlamaIndex or AutoGen) and practical understanding of RAG embeddings and vector databases.

Familiarity with data catalog/lineage concepts MCP (Model Context Protocol) or transformation/platform product roles in a large matrixed organisation.

Experience with procurement processes and platforms (e.g. Source-to-Contract Procure-to-Pay or vendor management systems).

Maersk is committed to a diverse and inclusive workplace and we embrace different styles of thinking. Maersk is an equal opportunities employer and welcomes applicants without regard to race colour gender sex age religion creed national origin ancestry citizenship marital status sexual orientation physical or mental disability medical condition pregnancy or parental leave veteran status gender identity genetic information or any other characteristic protected by applicable law. We will consider qualified applicants with criminal histories in a manner consistent with all legal requirements.

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About Company

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Maersk Line is a Danish international container shipping company and the largest operating subsidiary of the Maersk Group, a Danish business conglomerate. It is the world's largest container shipping company by both fleet size and cargo capacity, serving 374 offices in 116 countries

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