What does Pedro Pizarro Diaz do?

Pedro Pizarro Diaz is an AI Delivery Manager with 14 years in software delivery. He runs multi-team delivery across 5+ concurrent workstreams, builds AI agents and agentic pipelines deployed in production, and embeds AI into sprint rituals. He has worked across banking, aerospace, energy, and AI startups.

What results has Pedro Pizarro achieved as an AI Delivery Manager?

Pedro Pizarro has achieved +85% sprint commit rate, reduced cycle time by 50%, and built AI workflows now used daily by 40+ professionals. He has 14 years of delivery experience across complex multi-team environments.

Is Pedro Pizarro Diaz available for remote work in Europe?

Yes. Pedro Pizarro Diaz is based in Italy and available for remote EU engagements. He works with European and international companies as an AI Delivery Manager.

What methodologies does Pedro Pizarro use?

Pedro Pizarro is certified in SAFe 6 (SA), PSM II (Scrum), and ICF ACSTH coaching. He applies Lean-Kanban, Scrum, and SAFe frameworks, customizing delivery approaches to each team's context rather than applying rigid templates.

What AI tools and frameworks does Pedro Pizarro work with?

Pedro Pizarro works with Claude AI (Anthropic API), LLM governance frameworks, agentic pipelines, and custom AI assistants embedded in delivery workflows. He published Inverting Prompting (2024), a framework for AI-augmented sprint ceremonies.

What has Pedro Pizarro Diaz published?

Pedro Pizarro Diaz has published three works: Inverting Prompting: An Application of Carl Jacobi's Principle of Inversion in AI (2024), Synergizing Artificial and Emotional Intelligence (2024), and AI, Family, and Educational Change: Rethinking the Parenting Role (2025). All are available via ORCID: 0009-0005-8714-8976.

How can I contact Pedro Pizarro Diaz?

Pedro Pizarro Diaz can be reached at pedropizarro@live.it or +39 376 131 0537. His LinkedIn profile is at linkedin.com/in/pedro-pizarro-diaz and his portfolio is at pedropizarrodiaz.it.

Pedro Pizarro — AI Delivery Manager

Pedro Pizarro.

I ship software. Teams actually deliver.

14 years managing delivery across banking, aerospace, energy, and AI startups. Not theory. I've owned release pipelines, fixed broken backlogs, and embedded AI into sprint rituals that 40+ people now use daily. I work where execution matters more than slides.

Experience

2022 – Now BIP Consulting Banking · Insurance
Energy · Public Sector
Logistics · Home Appliances

AI Delivery Manager

End-to-end delivery across 5+ concurrent workstreams: backend, frontend, mobile iOS/Android, QA, design
Owned release pipelines with quality gates: UAT, NRT, BDD. No release without validated acceptance criteria.
Coordinated API integration delivery (REST, Swagger/OpenAPI) across internal and external services
Mobile banking app delivery: backend API dependencies, QA cycles, staged rollouts
AI delivery (2025): Designed and deployed a two-agent pipeline into live sprint workflows. The first agent, a Gemini Gem, reads ceremony transcripts from Google Drive and grounds every answer on verified sources before anything moves forward. The second agent takes that context and writes the full backlog: epics, user stories, acceptance criteria, QA criteria, ready before the team sits down. Results: +40% sprint capacity per cycle, cycle time from 6 days to 3, 85% commitment rate across 4 service lines.
AI delivery (2026): Designed a 4-phase AI agent adoption program for a large-scale software development cycle. The starting problem was documentation: most microservices had no updated technical docs, so dependency conflicts surfaced during development instead of before it, and AI agents working without context produced unreliable output. Phase 0 embeds Copilot instruction files in Git repositories. Phase 1 runs documentation agents that draft technical docs per microservice, validated by engineers before anything goes live. Phase 2 introduces a pre-development agent that reads those docs and flags conflicts before the first commit. Phase 3 adds a post-PR agent that proposes documentation updates after each merge. Currently running on 23 pilot microservices. Trained 40+ professionals and built the LLM governance framework that governs every step.

2021 – 2022 AizoOn Aerospace
DevOps · CI/CD

Agile Lead

Coordinated delivery across 4 teams (~30 members) on a compliance-audited aerospace SaaS product
Improved release frequency: bi-monthly → every 3 weeks via CI/CD optimization in Azure DevOps
Built early-warning monitoring and auditable decision logs aligned with aerospace compliance

2019 – 2021 CWS Digital Solutions Corporate Training
Distributed Teams
Italy / India

Scrum Master

Distributed teams across Italy and India: 5-6h daily overlap, structured async communication
Lead time cut from 3 weeks → 1.5 weeks (−50%) via custom Lean-Kanban system
Led product discovery for custom CRM: 30+ user interviews, MVP workshops, integration requirements

Capabilities

Delivery & Planning

Release Management
Sprint Planning & Grooming
Backlog Hygiene
Estimation & Refinement
Risk Tracking
WIP & Flow Metrics
DORA Metrics

Technical Stack

Jira (full config + migration)
Azure DevOps · CI/CD
GitHub workflows
REST APIs · Swagger/OpenAPI
BDD · UAT · NRT
N8N · API integration

AI in Delivery

Custom AI Agents
Agentic Workflows
Multi-Agent Pipelines
LLM Governance
Human-in-the-Loop Validation
RAG / Vector Embeddings
Claude · Gemini Gem · ChatGPT
n8n · API integration
Inverting Prompting (published)

Frameworks

SAFe 6
Scrum / Scrum Nexus
Kanban · Lean
DevOps
ITIL Foundation

Domains

Mobile Apps · SaaS Platforms
Backend · Frontend · QA
Banking · Aerospace
Energy · Insurance
Public Sector · AI Startups

Languages

Italian: Native
Spanish: Native
English: C2

Certifications

2026 Claude with the Anthropic API

2025 Certified SAFe 6 Agilist

2024 Professional Scrum Master II (PSM II)

2024 Professional Certified Coach (ICF ACSTH)

2024 Asana Workflow Specialist

2023 CI/CD Solutions with Azure DevOps

2021 Agile with Atlassian Jira

2020 Professional Scrum Master I (PSM I)

Writing

2024 Prompt Engineering

Inverting Prompting: An Application of Carl Jacobi's Principle of Inversion in AI

Applies Carl Jacobi's inversion principle to AI prompt engineering. Instead of prompting directly toward a goal, the opposite is prompted first, surfacing failure modes and hidden variables, then refined into a precise, effective prompt. Demonstrated in training and delivery contexts.

2024 AI · Agile · Leadership

Synergizing Artificial and Emotional Intelligence

Explores how Emotional Intelligence (EI) and AI work together in fast-paced Agile environments. Covers conflict resolution, adaptive leadership, and team performance through case studies, arguing that EI is the distinctively human complement to AI's analytical power.

2025 AI · Education · Parenting

AI, Family, and Educational Change: Rethinking the Parenting Role

Examines how AI integration into family life is transforming the parental role. Proposes a "parental emotional mediation" framework, adapting Goleman's emotional intelligence theory to the digital age, with practical tools like the "candy test" and "emotional traffic light."