Solutions Architect · Cloud-Native Systems · Enterprise AI · Strategic Foresight

I am a Solutions Architect actively exploring international relocation and migration opportunities. I am open to a suitable job offer with visa or relocation support and willing to move for the right team, problem, and long-term opportunity. Over 5+ years, I've worked from discovery and systems modeling through Python services, enterprise integrations, Kubernetes deployments, and production AI automation. I turn business goals and constraints into architecture that teams can build, operate, and evolve.

My PhD work in Futures Studies adds a longer horizon to those decisions. I study technology megatrends, uncertainty, and the forces shaping future organizations, then use scenario thinking to test architectural choices before they become expensive commitments. The goal is practical: build for today's constraints while keeping tomorrow's options open.

def my_approach(signal, constraint):
    problem = find_root_cause(signal)
    architecture = design_for_change(problem, constraint)
    return ship_observe_improve(architecture)

• Discover before designing: clarify the business outcome, users, constraints, risks, and measurable definition of success.
• Translate across boundaries: connect product, engineering, security, operations, data, and leadership through shared models and explicit trade-offs.
• Design for change: choose modular boundaries, integration contracts, observability, and deployment patterns that keep future options open.
• Make architecture executable: turn principles into diagrams, ADRs, roadmaps, proof-of-concepts, implementation guidance, and operational ownership.
• Stay close to production: validate assumptions with working services, delivery metrics, feedback loops, and post-launch learning.

I am especially interested in roles where architecture sits close to cloud platforms, distributed systems, enterprise integration, AI enablement, and digital transformation. I can contribute across the full path from problem framing and target architecture to delivery, adoption, and continuous improvement.

Futures research helps me ask better architecture questions: Which signals should we monitor? Which assumptions are fragile? What happens if regulation, customer behavior, infrastructure cost, or AI capability changes faster than expected? I use horizon scanning, systems mapping, scenario planning, and backcasting to create resilient decision pathways rather than a single brittle forecast.

That perspective complements engineering discipline. A future-ready architecture is not one that predicts the future perfectly; it is one that can sense change early, absorb uncertainty, and adapt without forcing the organization to start over.

Solutions Architect — Cloud, Systems & AI · Sep 2025 – Present

• Architect cloud-native internal services on Docker and Kubernetes with Helm, with attention to resilience and repeatable deployment.
• Build Python/SQL services and enterprise identity and authorization flows for a platform serving 1,000+ internal users.
• Deliver production LLM and RAG automations for document triage; deploy 10+ services through GitHub Actions CI/CD.
• Lead discovery, architecture, and rollout for digital LMS and HR infrastructure across business units.

Solutions Architect — Workflow, Systems & Integration · Nov 2023 – Sep 2025

• Designed Jira workflow automations, data models, and leadership dashboards using ScriptRunner and Jira Assets.
• Connected Jira, GitLab, Confluence, SQL Server, and Recruitee through an integration ecosystem orchestrated with n8n across 6+ APIs.
• Scoped helpdesk, process, and data platform extensions through fit-gap analysis.

Solutions Architect — Organizational Systems & P&OD · Jun 2023 – Jan 2024

• Diagnosed recurring process failures with analytics and systems modeling, then turned onboarding and administrative work into reproducible digital workflows.

• Cloud-native infrastructure: production Docker/Kubernetes services with Helm and automated GitHub Actions delivery.
• AI document triage: LLM, RAG, vector database, and LangChain components orchestrated inside an operational workflow.
• Enterprise integration: Jira, GitLab, Confluence, SQL, and n8n connected through governed APIs.
• Decision support: Power BI monitoring and CNN/MLflow experiments for pricing optimization.
• Open work: real-time subtitle translator, Jira MCP guide, and Python automation.

My research covers technology megatrends, digital entrepreneurship, system dynamics, and future-ready organizations. The MBA thesis focused on HR technology trends and entrepreneurial opportunities; my electrical engineering project was a GPS design with Arduino.

Open to international relocation for the right job offer · Remote collaboration welcome · Full résumé · Get in touch

_{Signals → scenarios → architecture → systems that adapt.}