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Vetted Prometheus Professionals
Pre-screened and vetted.
Hongxi Chen
Intern Software Engineer specializing in distributed systems and backend infrastructure
“Backend engineer with deep experience building event-driven logistics systems (orders, warehouse execution, real-time delivery tracking) using Spring Boot/PostgreSQL/Redis and strong observability (Prometheus/Grafana). Led a zero-downtime migration from monolithic MySQL to a sharded architecture for ~2M users with dual-write, checksum validation, and fast auto-rollback, and has strong security expertise including PostgreSQL RLS for multi-tenant SaaS and robust OAuth/JWT handling.”
Rahul Kushwaha
Mid-level Software Engineer specializing in FinTech and scalable microservices
“Backend/platform engineer focused on high-traffic financial systems, owning real-time event-driven ingestion and Kafka streaming pipelines using Python/FastAPI, Avro schemas, and AWS services. Has hands-on Kubernetes (EKS) and GitOps/CI-CD experience (ArgoCD/Jenkins) and supported large-scale migrations from legacy VMs to containerized microservices with zero/low-downtime cutovers.”
Keerthana Chinthalapally
Senior Full-Stack Developer specializing in cloud-native microservices
“Bank of America engineer/product owner who built a real-time transaction insights and spending categorization platform using React/TypeScript and Spring Boot microservices with Kafka. Deep experience in event-driven architectures, performance tuning at peak banking loads, and reliability patterns (SLOs, observability, feature flags, DLQs). Also created an internal monitoring/alerting tool adopted across engineering and ops, cutting incident response time by 40%+.”
Pratik Jaiswal
Mid-level AI/ML Engineer specializing in financial services ML and MLOps
“ML engineer/data scientist with M&T Bank experience who built a production reinforcement-learning portfolio analytics tool for wealth management, emphasizing near real-time performance via batch/serving separation and robust generalization through stress-scenario backtesting and RL regularization. Strong MLOps background (Airflow, Grafana, MLflow) and proven ability to drive adoption with non-technical stakeholders using KPI alignment and SHAP-based explanations.”
Staff Machine Learning Engineer specializing in LLM agents and ML systems
Mid-level Software Engineer specializing in cloud-native microservices and real-time data pipelines
Senior Full-Stack Java Engineer specializing in cloud-native microservices and FinTech integrations
Mid-level Full-Stack Developer specializing in Python and React for e-commerce
Senior Software Engineer specializing in web and mobile applications
Mid-Level Software Development Engineer specializing in cloud-native backend systems
Mid-level Full-Stack Developer specializing in Python, React, and cloud-native AI microservices
Mid-Level Software Engineer specializing in cloud-native backend and LLM/RAG systems
Mid-level DevOps & MLOps Engineer specializing in cloud-native CI/CD and Kubernetes
Senior Software Engineer specializing in backend microservices and AI/ML integrations
Mid-level DevOps Engineer specializing in multi-cloud Kubernetes and CI/CD automation
Senior DevOps Engineer specializing in cloud-native CI/CD and Kubernetes
Senior Full-Stack Java Developer specializing in microservices, cloud, and real-time systems
Mid-level Data Scientist specializing in ML, MLOps, and forecasting for FinTech and AI hardware
Mid-level AI/ML Engineer specializing in NLP, MLOps, and compliance-focused ML systems
Mid-Level Full-Stack Software Engineer specializing in cloud-native microservices
Mid-level Site Reliability Engineer specializing in Kubernetes observability and cloud infrastructure
Senior Software Engineer specializing in backend systems and AI-driven automation