SIDDHANT PORWAL
I’m Siddhant Porwal, an AI Solutions Architect and MSCS student at USC, focusing on sovereign infrastructure, multi-agent orchestration, and stateless bridge architectures.
About
I’m Siddhant Porwal, an AI Solutions Architect and MSCS student at USC, focusing on sovereign infrastructure, multi-agent orchestration, and stateless bridge architectures. I design secure, compliant RAG systems (RAFT) and MCP-based registries for GovCloud and highly regulated environments, with a track record of optimizing high-performance JAX/C++ inference kernels and mission-critical agentic tooling.
Currently building data pipelines and experimental AI tooling at USC and ARIS Labs, bridging enterprise data with LLMs, and delivering real-world RAG tooling and compliance solutions for federal programs. I enjoy tackling hard engineering problems at the intersection of AI, systems, and policy, and I value practical, privacy-preserving designs.
- 2 years' experience
- Joined April 2026
Industry experience
- Software & Internet
- Government
- Education
- Professional Services
- Media & Entertainment
Work experience
Architected the ARIS Protocol: a Stateless Bridge infrastructure for secure, sovereign AI deployment in regulated environments, ensuring zero data residency and maximum privacy. Engineered a modular Metadata Catalog (MCP) Registry for real-time tool injection, enabling LLMs to interact securely with legacy enterprise ontologies, ETL pipelines, and internal databases. Developed BidSmith: a multi-agent orchestration engine for federal RFP compliance, utilizing LangGraph to automate compliance matrix extraction and high-dimensional document analysis.
Developing data pipelines for multimodal auditory research, implementing parallelized signal processing modules in C++ with Python bindings to handle TB-scale datasets. Optimized ingestion throughput by 32%, enabling faster iteration for experimental voice modeling and Transformer-based ranking/retrieval tasks using Apache Spark.
Engineered a real-time event streaming service using Kafka and Java, handling 50k+ transactions per second. Optimized database queries for internal risk dashboards, reducing data retrieval latency by 35% via indexing.
Education
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