Vetted Prometheus Professionals

Geetha Sri Kasu

Screened

Mid-level Software Engineer specializing in Java/Spring Boot, Kafka, and AWS

5y exp

“Software engineer who owned an end-to-end self-service reporting workflow (secure APIs, async/batched processing, and React UI), improving report generation performance by ~30–40% and reducing manual support effort. Also built a RAG/embeddings prototype over internal docs and service logs with grounding-focused guardrails, and has a strong reliability/observability mindset (retries, DLQs, CI/CD validation, dashboards/tracing) for distributed workflows.”

Mustafa Ali

Screened

Mid-level Software Engineer specializing in backend systems and AI

Boston, MA4y exp

“Founding/early backend engineer at ATICA Global who built the company's core hotel property management platform from an empty repo into a production system used by 500+ hotel clients. Combines strong backend architecture with pragmatic product execution, including a dynamic pricing engine that increased partner revenue 17% YoY and an AI-powered sentiment pipeline processing 200K+ reviews/month.”

“ML/AI engineer with strong end-to-end production ownership across predictive ML and Generative AI use cases. They built a churn prediction platform that cut churn 12% and preserved about $1.2M in annual revenue, and also shipped a RAG-based support assistant that reduced ticket resolution time 30% while improving agent satisfaction and onboarding speed.”

Yash Patel

Screened

Mid AI/ML Engineer specializing in MLOps and cloud platforms

Texas, USA3y exp

“ML/AI engineer with strong end-to-end production ownership across classical ML and GenAI systems. Built and deployed predictive analytics and RAG-based internal tools on AWS/Kubernetes with measurable impact on accuracy, latency, deployment speed, safety, and user productivity.”

“Backend/platform engineer with experience at Fidelity and PayPal, spanning financial systems, payment pipelines, and regulated AI workflows. They’ve owned large-scale deployments end-to-end, including a brokerage platform for 150,000+ accounts, and have hands-on experience integrating OpenAI into internal research tooling with compliance-safe validation and human review.”

“Engineering leader focused on multi-cloud platform modernization, combining deep hands-on expertise in Kubernetes, Terraform, GitOps, and DevSecOps with management of 18-person DevOps/SRE/software teams. Particularly strong in building secure, scalable enterprise SaaS infrastructure and Spark/Databricks data platforms while driving cross-functional standardization, reliability, and faster release cycles.”

Vijayagopalan Raveendran

Screened

Principal Enterprise Architect specializing in AI, cloud, data, and FinTech transformation

Jersey City, NJ20y exp

“Solutions/technical consulting professional with enterprise experience supporting major accounts including Costco, MasterCard, Delta Dental of Michigan, and Fannie Mae. Brings a blend of cloud migration, enterprise architecture, security/IAM integration, and business-case development, plus hands-on automation work in Python and GCP to modernize sales-related data processing.”

“Shopify full-stack engineer focused on AI/LLM-powered merchant automation products. They have hands-on experience building React/TypeScript and Python/FastAPI systems for long-running agentic workflows, including orchestration, guardrails, observability, and customer-facing trust features, with measurable gains in task completion and latency.”

“Full-stack engineer with early-stage startup experience at Compass, working across backend services, data pipelines, and React applications in a fast-moving real estate platform. Stands out for combining hands-on systems work—like a Kafka/Python ingestion pipeline that cut latency 35%—with product impact, including dashboard workflow changes tied to a 12% lift in lead conversion.”

“ML/AI engineer with hands-on ownership of both classical ML and GenAI systems in production. They built an end-to-end churn prediction service on AWS and also shipped RAG-based document search/summarization features, with clear experience in monitoring, hallucination reduction, cost/latency optimization, and creating shared Python/LLM infrastructure used across teams.”