Ateet Vatan Bahmani

Leading architecture and end-to-end development of a large-scale Deterministic AI platform focused on predictable,

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auditable, and intelligent workflows. Architected a modular, execution-driven AI system with a single deterministic execution spine, coordinating orchestration, context management, knowledge processing, reasoning, and multi-model validation. Designed agent orchestration patterns enforcing execution order, context propagation, budget control, fault isolation, and confidence scoring. Implemented MCP-based tool integration and A2A agent communication protocols for cross-system interoperability. Enforced security and compliance standards aligned with ISO 27001 and GDPR, including RBAC, secrets vaulting, audit logging, and data isolation. Built workflow automation pipelines using n8n for scheduling, event-driven triggers, data routing, and agent orchestration. Built multi-database AI infrastructure (relational, document, graph, vector, cache) to support persistent reasoning state and continuous learning. Hands-on Python lead, defining core abstractions, data contracts, and CI/CD standards. Leading technical delivery, interviewing, mentoring, and guiding engineers and interns.

Transitioned into AI Engineering through Masterschool Institute of Technology, Berlin, followed with independent

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freelance-style project execution. Designed and engineered three AI platforms (mainly Python): Med AI (Healthcare Automation), MASX AI (Geopolitical Forecasting), and Echo AI (Personal AI Clone). Delivered functional AI prototypes showcasing expertise in multi-agent systems, real-time data pipelines, RAG architectures, and LLM integrations.