I'm Sepehr Rezaee, a Senior AI Architect specializing in agentic LLM systems, retrieval-augmented generation, and safety-first platforms with 5+ years of experience designing and operating production multi-agent services.
- π« BSc in Computer Science, Shahid Beheshti University (2021β2025)
- ποΈ AI Engineer, Agentic Systems @ PropTy Global, Dubai (2024β2025)
- π§ Research Intern @ Mathis Lab, EPFL (2025)
- π Chief AI Officer & Multi-Agent Architect @ Novel Mind Scientist, Tehran (2022β2025)
My focus areas:
- AI Architecture & Multi-Agent Systems: Designing scalable production multi-agent services with SLOs, error budgets, and cost/latency controls
- RAG Platforms & Safety: Building retrieval-augmented generation systems with enterprise-grade governance and security
- MLOps at Scale: Orchestrating reliable AI systems with Docker/Kubernetes, monitoring, and observability
- AI Security & Research: Translating research on model security and evaluation into production practices
See more in my CV.
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AI Engineer, Agentic Systems @ PropTy Global (Dubai, 2024β2025)
- Architected multi-agent systems (LangChain + custom RAG) for autonomous recommendations/decisions
- Achieved 85%+ end-to-end task completion in business workflows
- Implemented agent-to-agent protocols and memory for context-aware planning and goal execution
- Productionized on Docker/Kubernetes with sub-100ms API path for critical endpoints
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Chief AI Officer & Multi-Agent Architect @ Novel Mind Scientist (Tehran, 2022β2025)
- Led delivery of LLM-powered agents across SaaS/health/education with measurable SLAs
- Scaled multi-agent orchestration (LangChain, Celery) and automated business processes
- Drove engineering standards (docs, ADRs, onboarding guides) to accelerate adoption
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Research Intern @ Mathis Lab, EPFL (Switzerland, 2025)
- Co-authored ICCV 2025 accepted paper on DISTIL: data-free diffusion-based trigger inversion for Trojaned models
- Achieved new SOTA on BackdoorBench (+7.1% acc) and object-detection scanning (+9.4%)
- Built latent-diffusion pipelines with classifier-guided feedback to expose adversarial vulnerabilities
- Agent Orchestration: LangChain, LangGraph, LlamaIndex, Multi-Agent Systems, RAG, SPAR (Sense-Plan-Act-Reflect), Prompt Engineering
- Programming: Python (expert), C++, Java, C#
- Infrastructure: Docker (expert), Kubernetes (expert), AWS (SageMaker, EC2), GCP, Azure
- Databases/Vector: Pinecone, Weaviate, Chroma, PostgreSQL (pgvector), MongoDB, Redis
- LLMs: OpenAI GPT-3/4, Anthropic Claude, Google Gemini, HF Transformers
- MLOps & Services: MLflow, Airflow, Celery, Prometheus, Grafana, ELK, FastAPI, Flask, REST/GraphQL
- Other: Knowledge Graphs (Neo4j), Multimodal AI, Speech/Text Interfaces, SaaS Architecture
- DISTIL: Data-Free Inversion of Suspicious Trojan Inputs via Latent Diffusion (ICCV 2025, accepted)
- Scanning Trojaned Models Using Out-of-Distribution Samples (NeurIPS 2024, accepted)
- Comparison of Pre-Training and Classification Models for Early Detection of Alzheimer's Disease Using MRI (I4C 2023)
- Best Ideator Award: National Young Scientists Festival (2023)
- Top 0.2% National Entrance Exam: Placed 352nd out of ~150,000 (2020)
- Email: [email protected]
- GitHub: SepehrRezaee
- LinkedIn: linkedin.com/in/sepehr-rezaee/
- Personal Website: sepehrrezaee.com

