Nick Cerutti

Independent contract engagements · Paused Jan.-Jul. 2026 during the trading role · NDA-bound

• Brought in across 6+ fast-growing platforms, from Series B to late-stage teams, to build the multi-tenant substrate for agent systems serving 250-450 concurrent instances across AWS Bedrock, AgentCore, and Azure environments.
• Led incident response for a production multi-agent cost explosion projected at $40K+ per day, implementing circuit breakers, per-session spend caps, and retrospective governance controls within 72 hours with no recurrence reported during the engagement.
• Defined Service Level Objective (SLO) frameworks across 3 client platforms using task completion rate, mean tool calls, hallucination escape rate, and end-to-end latency; improved SLO compliance from 71% to 96% over two quarters.
• Audited and built retrieval and governance systems supporting 1.8M+ tool invocations, with deterministic policy validation and no known bypasses reported in those deployments using Pinecone and OpenSearch.
• Built Go, Python, and TypeScript middleware, Azure DevOps templates, and deployment automation for 4 distributed engineering teams, reducing release-cycle overhead by roughly 40%.
• Refactored client integrations with Anthropic SDK, n8n, and Copilot Studio to enforce token optimization, caching, and low-infrastructure patterns, delivering an aggregate $200K annual reduction in cloud and LLM spend.
• Standardized data lakes and model registries across 2 client platforms, integrating Databricks and Domino Data Lab with classical ML workloads in scikit-learn, PyTorch, and TensorFlow.

• Designed and ran in production a real-time trading system for prediction markets, using event-driven Python and Rust pipelines to pull live data from centralized exchanges and on-chain sources while holding sub-10ms latency at peak load.
• Designed the risk-control layer for live trading with position limits, daily loss limits, and slippage checks, cutting execution slippage by 14% with zero limit breaches while trading real capital.
• Built statistical models of market order flow to detect volatility clustering and used them to size trades and set execution pace under fast-moving conditions.
• Built Kelly-criterion-based position sizing that scales exposure to model confidence, reducing tail losses in high-uncertainty periods without giving up long-run expected value.
• Maintained a research pipeline covering historical backfill, detector-faithful backtesting, walk-forward validation, and automated signal outcome labeling.

• Contributed to a seven-engineer MLOps pod, spearheading the enterprise deployment and evaluation infrastructure while ensuring pipeline reliability across containerized LLM and inference workloads in production.
• Deployed and operated a multi-GPU Triton Inference Server cluster with dynamic batching and model quantization for NLP and Computer Vision pipelines, defining inference SLOs and Prometheus/Grafana alerting runbooks for OOM failures.
• Led the decomposition of a monolithic FastAPI inference service into event-driven microservices with Docker, PostgreSQL, and Kafka, reducing cold-start deployment time from 18 minutes to under 4.
• Owned schema and indexing strategy for behavioral analytics datasets used by 3 cross-functional product teams, driving p99 query latency from over 900ms to 120ms through index and materialized-view redesign.
• Engineered GitOps-driven CI/CD with GitHub Actions and ArgoCD, automated health checks, and canary rollout policies, sustaining 99.9% uptime across production containerized environments.

• Assisted the core infrastructure team in containerizing legacy monolithic applications with Docker for smoother development and staging transitions.
• Wrote Python and Bash automation scripts to clean, parse, and ingest semi-structured log data into staging databases, accelerating debugging workflows.
• Configured Prometheus and Grafana monitoring for server health, memory allocation, and API latency, while optimizing relational schemas and SQL queries for internal analytics dashboards.