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Vetted Prometheus Professionals
Pre-screened and vetted.
Senior Full-Stack Engineer specializing in cloud-native .NET microservices
Mid-level AI/ML Engineer specializing in GPU-accelerated LLM and vision systems
Staff Software Engineer specializing in FinTech, AI/ML, and cloud microservices
Senior AI/ML Engineer specializing in personalization, recommendations, and forecasting
Mid-level Site Reliability Engineer specializing in AI training infrastructure and GPU platforms
Mid-level AI/ML Engineer specializing in LLM fine-tuning and RAG systems
Senior DevSecOps Engineer specializing in multi-cloud CI/CD and federal compliance
Senior Software Engineer specializing in AI/LLM and distributed cloud systems
Senior Full-Stack Engineer specializing in AI/ML, LLMs, and RAG systems
Mid-level Machine Learning Engineer specializing in LLMs, RAG, and GPU-accelerated cloud systems
Mid-Level Backend Software Engineer specializing in FinTech and cloud-native platforms
Staff Full-Stack Software Engineer specializing in scalable web platforms and cloud infrastructure
Mid-level Full-Stack/Backend Software Engineer specializing in distributed systems and cloud
Senior Data Engineer specializing in cloud data platforms and real-time analytics
Junior AI Software Engineer specializing in LLM systems and retrieval (RAG)
Mid-level Software Engineer specializing in backend systems, billing, and real-time data pipelines
Principal Data Scientist / AI Engineer specializing in healthcare-native AI platforms
Senior Azure DevOps Engineer specializing in cloud architecture, IaC, and DevSecOps
Rhutwij Tulankar
Engineering Manager and ML/Data Architect specializing in scalable data platforms and personalization
“Hands-on engineering manager at a marketing company leading a highly senior, distributed team (10 direct reports) while personally coding ~60–70% and owning end-to-end architecture across three interconnected products. Built agentic CRM automation and a reinforcement-learning-driven distribution layer for channel spend/bidding, with a strong focus on scalable design and observability (Prometheus/APM/logging) enabling frequent releases and few production incidents.”
Vigynesh Bhatt
Mid-level Software Engineer specializing in backend, cloud, and ML systems
“Software engineer with experience across Goldman Sachs, BYU Broadcasting, Juniper Networks, and an edtech startup (Doubtnut), spanning data migrations, AWS-based media backends, and microservices observability. Built a Redis/ElastiCache caching layer in front of DynamoDB/S3 to improve media delivery latency and cost, and created an SEO indexing automation tool using the Google Search Console API that saved ~15–30 person-hours per day.”