Vetted Express Professionals

Lavanya Chilakalapudi

Screened

Mid-level Full-Stack Developer specializing in cloud-native web apps and APIs

Tampa, FL5y exp

“Backend engineer with experience building microservice-based systems that integrate LLM workflows (code review suggestions, documentation generation, test scaffolding) using REST APIs, Celery/Redis, and OpenTelemetry for observability. Demonstrates hands-on database and performance optimization in PostgreSQL/SQLAlchemy (bulk inserts, lock mitigation, cursor-based pagination) plus multi-tenant data isolation via tenant-aware models, middleware scoping, and schema/row-level strategies.”

“Engineering leader who has operated effectively in both a VC-backed startup and SAP, combining director-level org leadership with day-to-day technical depth. Notable for re-architecting integrations that produced a 3x revenue gain, leading a 90-engineer matrixed organization, and staying hands-on in GenAI, infrastructure, and full-stack problem solving.”

“Front-end/UI engineer who built and standardized a complex metadata component system for 2,500+ banking users across 40+ internal product surfaces. Stands out for combining design-system architecture, browser-level CSS expertise, and workflow-sensitive UX for demanding financial users, including a token system that resolved 488 style references and a reusable responsive component library adopted across five product areas.”

“Full-stack developer who built a learning management web app end-to-end using React, Spring Boot, and MySQL, integrating APIs via Axios and validating/testing with Postman. Has experience handling data-heavy workloads (courses, quiz results) and improving performance with pagination, and is comfortable designing microservice-style endpoints with CI/CD considerations.”

“Summer SDE intern at AWS who built and deployed a column-lineage debugging tool for on-call engineers, using AWS Bedrock to parse SQL and generate a column DAG. Integrated the tool into an existing validation system and hardened it against real-world SQL format differences via flexible parsing and testing with queries from multiple upstream teams.”

“Backend/data-systems SWE (2 years) who has built production ETL/streaming workflows (Kafka, Debezium, Elasticsearch) and troubleshot real SQL performance regressions caused by indexing/type issues. Also ships full-stack personal projects in Next.js App Router + TypeScript with Postgres, emphasizing reliability via constraints, idempotency, and strong observability (Grafana/Kibana).”

Manaswini Gogineni

Screened

Junior Software Engineer specializing in cloud infrastructure and full-stack web development

San Francisco, CA2y exp

“Full-stack/platform engineer who has owned real-time analytics products end-to-end and built scalable TypeScript/React + Node.js systems using event-driven and microservices architectures (Kafka/RabbitMQ). Also created a widely adopted Go CLI that standardized AWS/Terraform provisioning across multiple teams, cutting environment setup from days to minutes through opinionated defaults, documentation, and cross-org partnerships.”

“Backend/platform engineer with experience at Fidelity and PayPal, spanning financial systems, payment pipelines, and regulated AI workflows. They’ve owned large-scale deployments end-to-end, including a brokerage platform for 150,000+ accounts, and have hands-on experience integrating OpenAI into internal research tooling with compliance-safe validation and human review.”

“Backend-leaning full-stack engineer with Amazon production experience on book and author search suggestions, plus hands-on work integrating AI agents with Node.js, Bedrock, and OpenAI Assistants. Also built internal admin tools for safety training, OSHA compliance, and digital badge workflows, showing strength in turning ambiguous operational problems into practical shipped products.”

“Full-stack builder with hands-on experience spanning a MERN e-commerce product, an AI code review agent, and an ambiguous AWS internship project involving PyTorch/TensorFlow support in Redshift. Particularly interesting for recruiters because they combine product-minded engineering with AI agent reliability work, including CI/CD integration, telemetry via Weights & Biases, and measurable impact like 80% reduction in manual review effort.”

“ML/AI engineer with hands-on ownership of both classical ML and GenAI systems in production. They built an end-to-end churn prediction service on AWS and also shipped RAG-based document search/summarization features, with clear experience in monitoring, hallucination reduction, cost/latency optimization, and creating shared Python/LLM infrastructure used across teams.”