.png){kind=logo}
Vetted Prometheus Professionals
Pre-screened and vetted.
Krishna vamsi Dhulipalla
Mid-level Software & ML Engineer specializing in agentic LLM systems and ML infrastructure
“Built and deployed an LLM-to-SQL automation system in a closed/internal environment, using a retriever–reranker–validator architecture on Kubernetes with strong security controls (semantic + rule-based validation and RBAC), achieving 99% uptime and cutting manual query time ~40%. Also worked on genomic sequence classification and semantic search workflows, orchestrating data prep with Airflow, tracking/deploying with MLflow, and optimizing distributed multi-GPU training on a university Kubernetes cluster.”
Pavan Kalyan Reddy Gunamareddy
Mid-level Full-Stack Java Developer specializing in FinTech and Healthcare
“Backend/platform engineer in fintech/payments (NexaBank/NextBank/Nexon Bank) who has built Kafka-orchestrated Java/Spring Boot microservices around a PostgreSQL double-entry ledger. Led production-critical reliability work preventing duplicate payment postings via idempotency and offset sequencing fixes, and shipped real-time ML fraud scoring (Python model API + Redis caching) with rigorous evaluation/monitoring (Prometheus) and workflow automation for dispute resolution.”
Jayanth Amol Ergola
Mid-Level Software Engineer specializing in full-stack development and data engineering
“Backend engineer with production experience at KeyBank building high-volume Java/Spring Boot services on Azure with PostgreSQL/Oracle, including async job ingestion and tracking. Demonstrates strong reliability/performance debugging (HikariCP pool exhaustion, DB contention) and has shipped an LLM-powered data analysis/summarization feature with robust production guardrails (validation, shadow testing, deterministic fallbacks, audit logs).”
Manish Ravikanti
Mid-level Site Reliability Engineer specializing in cloud infrastructure and Kubernetes
“Backend/infra-focused engineer who owned production systems for distributed ML experimentation (hyperparameter tuning across a cluster with GPU scaling, custom scheduling, and checkpoint-based fault tolerance). Also built and operated a low-latency log validation service using queued async workflows with idempotency, retries/backoff, and strong observability, plus experience building resilient Selenium-based browser automations for complex multi-step web flows.”
Mid-Level Software/ML Engineer specializing in NLP, OCR, and fraud detection in FinTech
Mid-level Backend Software Engineer specializing in Python APIs and data engineering
Mid-Level Full-Stack Software Engineer specializing in Java, Python, and AWS
Junior Full-Stack Software Engineer specializing in cloud microservices and AI compliance
Senior DevOps & Cloud Platform Engineer specializing in SRE and multi-cloud Kubernetes
Mid-level Full-Stack Software Engineer specializing in cloud-native microservices
Junior Software Engineer specializing in backend systems and ML infrastructure
Mid-level Software Developer specializing in cloud-native automation and data pipelines
Mid-level Full-Stack Java Developer specializing in cloud-native microservices
Mid-Level Full-Stack Software Engineer specializing in FinTech and cloud-native microservices
Mid-Level Full-Stack Software Engineer specializing in React/Node.js and cloud systems
Mid-Level Machine Learning & Backend Engineer specializing in computer vision and robotics systems
Junior Systems/Backend Software Engineer specializing in distributed systems and low-latency pipelines
Mid-Level Software Engineer specializing in backend microservices and cloud infrastructure
Mid-Level Full-Stack Software Developer specializing in cloud-native microservices
Mid-level Cloud Engineer specializing in AWS, Kubernetes, and Terraform automation
Mid-level Software Engineer specializing in scalable backend systems and distributed data processing