No cost, no commitment - we'll make a personal intro
ST
Sravya Thotakuri
Mid-level Full-Stack Developer specializing in Healthcare and FinTech web applications
Fairview Health ServicesUniversity of DaytonRemote, USA4 Years ExperienceMid LevelWorks On-Site
Connect with Sravya
Sravya already has a relationship with Reval, so a warm intro from us gets a much better response than cold outreach.
Typically responds within 24 hours
Recommended
Already have an account?
About
Hands-on engineer focused on productionizing LLM-powered assistants: builds RAG pipelines with guardrails, response schemas, and citation-grounded outputs, then hardens them with explicit NFRs (latency, uptime, security, cost). Experienced diagnosing agentic/LLM workflow issues in real time using observability and stepwise isolation, and supports go-to-market via developer demos, workshops, and pre-sales technical evaluations in microservices/Spring Boot environments.
Hire with Reval
Find your next great hire
Our AI agents source, screen, and vet candidates for your open roles. Get qualified candidates within 48 hours.
Mid-level Full-Stack Developer specializing in cloud-native backend services and real-time data platforms
Remote, USA4y exp
NetflixUniversity of Dayton
“Backend/data engineering candidate with Netflix experience designing and migrating analytics platforms from batch to real-time streaming (Kafka/Flink) across AWS and GCP. Delivered measurable improvements (40% lower data delay, 99.9% accuracy) using phased rollouts, automated data validation (Great Expectations), and strong observability (Prometheus/Grafana), and proactively hardened pipelines with idempotency to prevent duplicate Kafka processing.”
Mid-level Full-Stack Developer specializing in cloud microservices and AI-driven FinTech
Remote, USA4y exp
StripeSouthern Arkansas University
“Stripe engineer who shipped an end-to-end merchant fraud insights dashboard, spanning Spring Boot/Kafka risk-scoring services and a React+TypeScript UI. Focused on low-latency, high-volume transaction processing and production operations on AWS (EKS/CloudWatch), including handling a real traffic-spike latency incident via query optimization, indexing, and rate limiting.”