Work

Experience

Coyote Technology Group is a newly formed firm. What follows is the experience our engineers bring to it: representative work from prior roles at large technology and information-services companies, described at the sector level. References are available on request.

Representative work

Zero-downtime deployment platform for a nationwide fleet

Prior role · Fortune 500 information services · Cloud, Modernization & IT Operations

Challenge

Software releases to thousands of client-facing nodes across the country were slow, manual, and risky, with outages during deployment windows.

Approach

Architected a high-performance, concurrent deployment and orchestration engine in Rust that coordinates large-scale releases across heterogeneous clusters with automated rollback and verification.

Outcome

Zero-downtime releases as the norm and 99.99% deployment reliability across the fleet.

Applied AI inside a legacy fraud-analytics platform

Prior role · Financial-crime analytics · Applied AI & Data

Challenge

A mature analytics product needed modern machine learning and large-language-model capabilities without a rewrite of the legacy systems it ran on.

Approach

Engineered and deployed a suite of real-time machine-learning microservices for transaction anomaly detection, and led pathfinding work integrating LLM and agentic AI workflows into the existing pipelines.

Outcome

High-precision detection of malicious transaction patterns in production and a modernized ML analytics pipeline that the product group continues to build on.

Automated hardware validation for prototype memory devices

Prior role · Global semiconductor manufacturer · Embedded, Electrical & OT

Challenge

Next-generation non-volatile memory prototypes required rigorous factory-floor validation, stress testing, and burn-in before they could ship, and existing tooling could not keep pace.

Approach

Built low-level C++ diagnostic and test-automation suites for production test floors, and worked directly with hardware teams to design and run experiments characterizing device behavior.

Outcome

Faster prototype evaluation and a repeatable validation framework that shortened time-to-market for new device generations.

Infrastructure-as-code modernization for global engineering datacenters

Prior role · Global semiconductor manufacturer · Cloud, Modernization & IT Operations

Challenge

Bare-metal server provisioning and configuration for high-performance-computing clusters was manual and inconsistent across a global Linux estate.

Approach

Delivered highly available infrastructure with automated configuration management, and built an infrastructure-as-code solution that overhauled rack landing and provisioning workflows.

Outcome

Deployment velocity improved by more than 300%, with consistent, auditable configuration across sites.

Embedded power-quality monitor

Independent hardware project · Power systems · Embedded, Electrical & OT

Challenge

Real-time visibility into power phase and harmonic conditions at the point of use, without a rack of bench instruments.

Approach

Designed a custom PCB in KiCad around an ARM Cortex-M4 microcontroller, with firmware performing real-time phase monitoring and harmonic analysis and reporting over a local mesh network.

Outcome

A working board-to-dashboard monitoring device: the same sensor-to-software path we apply to utility, facilities, and smart-city instrumentation.

Machine-learning load forecasting for power grids

Electrical engineering research · Power systems · Applied AI & Data

Challenge

Grid operators need to anticipate non-linear load flows under stressed conditions faster than conventional power-flow analysis allows.

Approach

Engineered a deep-learning model in Python to predict non-linear grid load flows and run predictive load analysis under constrained scenarios.

Outcome

A predictive analytics approach applicable to utility planning, demand forecasting, and infrastructure resilience work.

Technologies we have shipped with

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