Vetted Google Cloud Platform Professionals

“Capgemini engineer with 4+ years building and deploying high-availability, low-latency fraud detection APIs and multi-cluster distributed systems for a Fortune 20 bank, including zero-downtime production rollouts and multi-layer (SQL/network/hardware) performance debugging. Also built a Python + OpenAI/LangChain LLM-powered grading workflow for Austin School for Women, cutting feedback time from 90 minutes to 5 minutes per submission for 200+ learners.”

Dan Gervais

Screened ReferencesStrong rec.

Executive technology leader specializing in big data, AI/ML, and SaaS platforms

Escondido, CA28y exp

“Hands-on IT/engineering executive who has led high-impact architecture changes and compliance-driven data systems. Notably built an internally developed columnar database at Troparé (with dual-support UI for legacy/new DBs) and shipped an MVP in 3–4 months with dramatic performance improvements, and previously delivered PCI/opt-out compliant deletion workflows while addressing DB performance and migrations.”

“Current CTO of an analytics company in the eye industry that was acquired by a larger organization, and now exploring building a new analytics platform for individual provider offices. Focused on helping practices grow revenue and improve the patient journey to drive long-term retention, with entrepreneurial motivation tied to building a legacy business for their family.”

“Frontend engineer who built the full frontend for gameofstreaks.com using React/Next.js with an emphasis on responsive design, accessibility, SEO, and performance profiling. Has experience refactoring legacy HTML/CSS/JS sites into reusable React components and shipping quickly with unit tests, CI/CD, and branch-based deployments; also collaborates with designers in hackathon settings (e.g., an AI interview practice app).”

Emmanuel Ngalima

Screened ReferencesStrong rec.

Mid-Level Software Engineer specializing in geospatial AI and cloud security automation

San Ramon, CA5y exp

“Cloud engineer and cloud OS SME (Chevron) who productionized large-scale security remediation—using Tanium and Ansible to address CIS benchmark noncompliance across 5,000+ servers with robust logging and RCA handoffs. Also drives adoption of a geospatial AI refinery inspection product by consolidating siloed imagery into an enterprise geospatial database, and presents internally on agentic/LLM tooling (LangChain/LangGraph, LangSmith observability).”

Mounika Nadendla

Screened ReferencesStrong rec.

Senior Data Engineer specializing in cloud data platforms and real-time streaming

5y exp

“Data engineer focused on building reliable, production-grade data systems end-to-end: batch and real-time pipelines (Airflow/Kafka/Spark) with strong data quality, monitoring/alerting, and incident response. Has experience integrating external API/web data with retries, throttling, and schema-change handling, and serving curated datasets to analytics (Power BI) and backend consumers with performance optimizations like Redis caching.”

Mark Thomas

Screened ReferencesStrong rec.

Director-level software architect specializing in cloud, distributed systems, and healthcare IT

McCalla, AL20y exp

“Startup veteran with experience at seven companies since 2004 and direct exposure to Birmingham's Innovation Depot accelerator through three different startups. Has worked closely with investment teams on MVPs and pitch decks and brings a pragmatic lens to evaluating ventures through need, margins, burn rate, cash position, and sales growth strategy.”

Aldric Pinto

Screened ReferencesStrong rec.

Mid-level AI product and data lead specializing in analytics and healthcare AI

New Haven, CT4y exp

“Product-minded software engineering lead with a blend of backend, data engineering, cloud observability, and AI product experience. They’ve owned systems end-to-end, from ETL job builders that cut setup time 70% to hybrid-cloud observability workflows that reduced monitoring effort 80%, and also drove an AI marketing feature that improved conversion from 2% to 6%.”

Jayadeep Nukala

Screened ReferencesStrong rec.

Mid-level Software Engineer specializing in enterprise AI and FinTech integrations

San Francisco Bay Area, CA2y exp

“Built and deployed an enterprise AI testing solution at a startup, then customized and scaled it inside Citigroup over the course of a year to support 40+ projects and 1,000+ daily users. Brings hands-on production experience with multi-agent LLM workflows, RAG, enterprise deployment infrastructure, and real-world incident handling in AI-driven data pipelines.”

“Former CTO at Enodo who led development of programmatic parsers to extract unstructured data from real-estate financial documents (rent rolls and T12s), validating with users via prototypes before productionizing. Emphasizes accuracy-driven engineering and scalable test-suite growth based on real user samples, and has experience scoping complex product ideas (e.g., browser-based narrative editor) down to an MVP.”

“AI-focused product engineer working on LLM routing, prompt engineering, and multimodal API integrations at production scale. They describe improving system accuracy, latency, and token usage, fine-tuning an internal model to reduce third-party API dependence, and adding safety guardrails through prompt-injection testing and red-team evaluation.”

John Juszczak

Screened

Senior Software Engineer specializing in C++ tooling, CI/CD, and Unreal Engine pipelines

Los Angeles, CA10y exp

“Gameplay programmer with hands-on Unreal Engine multiplayer shooter experience, notably overhauling aiming/ADS using Enhanced Input and curve-table-driven response curves plus subtle aim assist. Demonstrates strong networking judgment (client-side prediction vs server authority for anti-cheat) and a systems mindset, adding automation/analytics to speed iteration and improve decision-making.”

Nithin Reddy

Screened

Mid-Level Software Development Engineer specializing in distributed systems and event-driven architectures

Santa Clara, California4y exp

“Built and maintained an internal JavaScript/React real-time event monitoring UI used by multiple Goldman Sachs teams (e.g., Private Wealth Management and Bulk Trading Systems). Focused on scaling performance under hundreds of events/sec—using profiling, memoization, batching, and debouncing—and paired it with strong internal documentation and disciplined incident diagnosis via synthetic load testing and logs/metrics.”