I am a senior architect delivering AI automation, secure decentralized infrastructure, and algorithmic trading engines. 5+ years shipping production-grade systems for funds, enterprises, and venture-backed founders.
Every engagement is architected for resilience, observability, and measurable ROI. I design secure data flows, deterministic execution paths, and rigorous deployment pipelines—so you get enterprise reliability with individual ownership.
I operate as a single-threaded owner across architecture, build, and optimization. My focus: intelligent automation, cryptographically secure systems, and execution-grade trading infrastructure. The outcome is strategic leverage with minimal overhead.
I map constraints across data, compute, security, and capital efficiency, then design architectures that stay robust under load and scrutiny.
Audit-ready code paths, observability-first instrumentation, and deployment practices aligned with regulated and high-stakes environments.
Every deliverable is tied to measurable outcomes: reduced operational drag, faster execution, safer capital flows, and clearer governance.
Deep, hands-on execution across AI systems, decentralized infrastructure, and automated trading. Each domain is handled end-to-end—from architecture to deployment.
Custom LLM tooling, retrieval pipelines, reinforcement-learning loops, and deterministic guardrails to reduce manual workflows and surface actionable insights.
Secure smart contracts, multi-chain bridges, and enterprise-grade nodes with rigorous testing and on-chain observability.
Low-latency execution stacks, market data engineering, and risk-managed automation spanning centralized and decentralized venues.
Representative scenarios demonstrating how I design, build, and optimize systems that hold up under production realities.
Designed a retrieval-augmented LLM platform with policy layers, human-in-the-loop validation, and spend telemetry. Reduced manual review by 62% and enabled auditable decision trails.
Architected smart contracts with formal verification targets, circuit breakers, and MEV-aware execution paths. Improved capital utilization while maintaining strict risk bounds.
Built a cross-exchange arbitrage stack with failover routing, kill switches, and live risk limits. Achieved consistent sub-25ms decision loops with deterministic logging.
Modernized market data ingestion with streaming transforms, feature stores, and drift detection. Increased signal freshness while cutting compute costs via adaptive batching.
Direct accountability, architectural depth, and a security-first mindset. I translate complex requirements into reliable, performant systems.
One lead from architecture to deployment—no handoffs, no dilution of responsibility.
Design-first approach with explicit threat models, data contracts, and SLOs before code is written.
Secure defaults, latency-aware patterns, and scalability baked into every layer—API, data, and infra.
Advisory-level collaboration with founders, CTOs, CIOs, and PMs to align technology with capital efficiency.
A selection of builds across AI automation, decentralized systems, and trading infrastructure. Each project reflects production constraints: performance, security, and operability.
End-to-end assistant for research, document processing, and reporting with retrieval, policy checks, and measurable cost controls. Built to be auditable, fast, and safe-by-default.
Event indexing, invariant checks, anomaly detection, and runbook-driven response flows.
Discuss this buildRisk-managed routing, deterministic logs, kill switches, and backtest-to-live pipelines.
Discuss this buildStreaming transforms, feature stores, and drift monitoring for production signal quality.
Discuss this buildTransparent, measurable stages—each with explicit deliverables, acceptance criteria, and operational safeguards.
Clarify objectives, constraints, compliance needs, and success metrics. Produce a concise architecture brief.
Design data flows, threat models, and SLOs. Select stack components mapped to performance and governance.
Implement services, contracts, and pipelines with automated tests, simulation, and observability baked in.
Harden environments, roll out gradually, monitor, and tune for latency, reliability, and cost.
Credentials and structured learning that back up my delivery across AI systems, decentralized infrastructure, and execution-grade engineering.
Coursera / DeepLearning.AI
Professional Training
Quant Program
Professional Certificate
Professional Certificate
Selected, proven tools chosen for security, performance, and operability—no unnecessary complexity.
For founders, CTOs, CIOs, and fund managers who need an accountable architect to design and deliver intelligent systems with security, performance, and clarity.