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Responsibilities
About the work:
- You will run the same AI product pattern across multiple countries, each with its own data sources, language and regulatory quirks.
- The core approach stays similar; the adaptation challenge is in the crawling of the data, and domain specifics.
- Your stakeholders span the AI Program team, IT Operations and the Regulation Team.
- The playbook and metrics you build will define how PST.AG scales AI products across its entire market.
What you will do:
- Take completed lighthouse AI projects and build a repeatable delivery template - pipeline configuration, evaluation datasets, prompt templates, release checklists, data source mappings and country-specific adaptation notes.
- Find opportunities for automation, AI agents and templates to make the project as repeatable and fast as possible.
- Run the template against multiple countries in sequence, adapting for language, data source variability and regulatory differences while keeping the core architecture unchanged.
- Maintain a living playbook capturing lessons from each replication - what needed adapting, what broke, data quality observations, evaluation edge cases.
- This will link directly to master requirements, which you will use as the source of truth.
- Manage the country rollout pipeline: prioritize by data readiness, business value and dependencies.
- Run formal change control per country.
- Coordinate AI engineers, AI developers, IT operations and country-domain experts across concurrent country replications.
- Identify when a country's data or regulatory conditions require a template change and escalate those to the AI Program Manager.
- Ensure evaluation and quality gates are run consistently across every country, with comparable results recorded.
- Drive continuous improvement: measure, publish and improve cycle time, accuracy, cost and coverage per iteration.
Required experience & competencies - Project management and repeatable delivery:
- 5+ years of project management experience, with demonstrable experience running multiple similar projects in sequence where each iteration improved on the last.
- Track record of creating delivery templates, playbooks or standardized processes that reduced cycle time, cost or error rate across repeated runs.
- Skilled in plan-vs-actual tracking, cycle time measurement, process documentation and formal change control.
- PMP, PRINCE2 or equivalent certification advantageous.
- Familiarity with the PMI Standard for AI in Portfolio, Program, and Project Management (2026) is a plus.
Required experience & competencies - AI literacy:
- Must be able to understand what an agentic AI system does, how it uses tools and retrieval, and what its quality characteristics are.
- Must be able to read and interpret evaluation metrics and use them to drive improvement.
- Must have exposure to MCP (Model Context Protocol) or similar agent-to-tool gateways.
Required experience & competencies - Process and continuous improvement mindset:
- Systematic approach to documenting what works, what does not, and how the next run should differ.
- Comfort with measurement and evidence-based decision-making.
- Structured documentation that would satisfy an audit or regulatory review.
- Everything is driven by requirements.
Personal competencies:
- Process orientation: you see every project as an instance of a process to be improved, not a one-off.
- Accountability: you hold teams to country delivery timelines.
- Precision: you write requirements, checklists and runbooks that leave no ambiguity.
- Patience with repetition: you take satisfaction in making the tenth run faster than the first.
Preferred experience:
- Familiarity with AI concepts - LLMs, RAG, agents, evaluation.
- Experience with international, multi-language or multi-jurisdiction delivery.
- Any delivery tooling (Jira, Linear, Confluence) and PM tooling (MS Project, Gantt).
- Bachelor's degree in Business Administration, Management, Industrial Engineering, Information Systems, Operations Management, Project Management or related field - or equivalent practical experience.
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