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Vetted Event-Driven Architecture Professionals
Pre-screened and vetted.
Mid-level Cloud Software Engineer specializing in AWS infrastructure and automation
Mid-level Python Developer specializing in AWS cloud-native backend systems
Mid-level Backend Engineer specializing in cloud-native microservices and AI-driven APIs
Mid-Level Full-Stack Software Engineer specializing in distributed systems and FinTech
Mid-level Backend Software Engineer specializing in Java microservices and cloud-native systems
Executive Technology Leader (CTO) specializing in AI-enabled SaaS and cloud transformation
Mid-level Full-Stack Java Developer specializing in cloud microservices and React
Mid-Level Software Engineer specializing in backend, microservices, and cloud platforms
Senior Data Engineer specializing in cloud lakehouse platforms for banking and healthcare
Senior Java Full-Stack Developer specializing in cloud-native FinTech and payments
Mid-level Python Backend Engineer specializing in cloud-native microservices and event-driven systems
Mid-Level Full-Stack Java Developer specializing in Spring Boot microservices and Angular
Bhuvaneswari Kudaravalli
Mid-Level Full-Stack Software Engineer specializing in TypeScript, React/Next.js, and Node/Nest APIs
“Full-stack engineer who built and scaled an AI-powered web product (React/Next.js + TypeScript/NestJS) with MongoDB, Redis, and RabbitMQ. Strong in rapid iteration while maintaining production quality—uses versioned APIs, feature flags, CI/CD, and observability (correlation IDs/structured logs) to ship frequently and debug distributed workflows. Also created an internal operations dashboard for real-time visibility and control of background jobs/AI workflows that was adopted quickly by ops and product teams.”
Sai Manikanta Kasireddy
Mid-level Machine Learning Engineer specializing in cloud-native GenAI and RAG systems
“Built and productionized an internal GenAI chatbot that makes company policy/SOP knowledge instantly searchable, using a secure RAG architecture on AWS (Bedrock/Titan embeddings/OpenSearch Serverless, Textract/Lambda/S3 ingestion, Claude 3 Sonnet). Demonstrates strong MLOps/orchestration experience (Airflow, Step Functions with Lambda/Glue/SageMaker) and a rigorous reliability approach (RAGAS metrics, A/B testing, citation validation, monitoring), including collaboration with compliance stakeholders via review dashboards.”
Rui Zhao
Junior Machine Learning Engineer specializing in semantic search and retrieval systems
“Built and shipped a production RAG system (“TROJAN KNOWLEDGE”) for answering questions over technical PDFs, using a 3-stage retrieval stack (BM25 + FAISS + cross-encoder) to lift F1 from 71% to 84%. Drove major performance gains with a 3-level cache (memory/Redis/disk) cutting latency from ~200ms to ~10ms, and added Prometheus/Grafana monitoring plus LangChain-based fallback logic to handle OpenAI rate limits under load.”
Nakul Reddy Sarasani
Junior Full-Stack Software Engineer specializing in cloud-native distributed systems
“Software engineer with JPMorgan Chase experience building a real-time operations console backend on Spring Boot/Kafka/Kubernetes and resolving peak-load latency through profiling, indexing, caching, and async processing. Also built and owned an AI-driven digital-archives metadata pipeline during a master’s at UNT using OCR + LLaMA-based prompting with validation, near-human accuracy, and human-in-the-loop guardrails.”
Deepika Chudi
Mid-level Full-Stack Engineer specializing in React, TypeScript, and Spring Boot
“Full-stack engineer with strong Next.js App Router/TypeScript experience who built production dataset search/filtering and data-heavy dashboards backed by Postgres. Demonstrates hands-on performance work across the stack (EXPLAIN ANALYZE, composite indexes, caching, React profiling/memoization) and has built durable, Temporal-like orchestrated data-processing workflows with idempotency and retry strategies in an early-stage startup environment (Gaia AI).”