Vetted Rate Limiting Professionals

Jayadeep Nukala

Screened ReferencesStrong rec.

Mid-level Full-Stack Engineer specializing in AI platforms and FinTech

USA3y exp

“Built full-stack and AI-driven products spanning banking KYC modernization and enterprise software testing automation. Particularly strong in productionizing LLM workflows in regulated environments, using deterministic orchestration, RAG, and human-in-the-loop controls to improve test coverage to 80% and reduce QA reporting burden by over 50%.”

“Full-stack/backend engineer with healthcare and enterprise experience: built and secured AWS-hosted services for a clinical EHR product that redacts/transforms hospital patient records for pharma customers (e.g., AstraZeneca, Johnson & Johnson). At Cisco, led an incremental Ruby-to-Python/Django migration for a compliance backend, and has deep multi-tenant security experience using Postgres RLS tied to JWT plus DLQ patterns to harden data pipelines.”

“Software engineer at Wrap who built production AWS Lambda services for large-scale Parquet dataset generation (50k+ records) and a synthetic traffic/lead generation system using Python, Playwright, and Jenkins. Also built and deployed a full-stack hobby product (MyAnimeListRanker) that ingests MyAnimeList user data and uses an Elo-based ranking workflow, with operational guardrails like rate limiting and monitoring via Vercel/logs.”

“LLM/agent engineer who shipped a production RAG-based recommendation + explanation system that replaced a traditional recommender stack, delivering ~20% CTR lift (and +8% after a reliability iteration) with strong cold-start performance. Demonstrates strong production rigor: schema-constrained generation, typed tool calling, explicit state/orchestration, deep monitoring/feedback loops, and safe integration with messy ERP inventory/order data using normalization, idempotency, and conflict-resolution guardrails.”

Yuan-Hao Chen

Screened

Intern Software Engineer specializing in backend systems and cloud infrastructure

Urbana, IL1y exp

“Backend-focused intern who owned real-time livestream features: live comment moderation using AWS Comprehend (sentiment/toxicity/PII) with safe fallbacks, plus AI-generated positive commentary via AWS Bedrock (Claude 3 Haiku). Emphasizes reliability/low-latency design, IAM troubleshooting, and disciplined GitOps-style CI workflows for reproducible deployments.”

Prateeksha Ranjan

Screened

Mid-level Software Engineer specializing in embedded AI and full-stack systems

Irvine, California4y exp

“Robotics software engineer who built and owned core navigation components for a TurtleBot in ROS/ROS2 and Gazebo, including an RRT-based planner, waypoint-to-velocity motion planning, and PID trajectory tracking. Demonstrates strong real-time debugging skills (control-loop timing under CPU load), costmap/occupancy-grid tuning, and distributed ROS2 communication design using DDS/QoS, plus Docker and CI/CD automation experience from Keysight.”

Vidhi Chhatbar

Screened

Mid-level Full-Stack Engineer specializing in cloud microservices and FinTech

Los Angeles, CA5y exp

“Software engineer with experience across enterprise (AIG, MSCI) and an early-stage startup (Job Map), owning production systems end-to-end. Built secure insurance microservices on Spring Boot with JWT/RBAC and AWS-based CI/CD/observability, plus Kafka streaming pipelines for financial data. Also shipped a GenAI personalization MVP using FastAPI and LLM APIs in a high-ambiguity startup environment.”

Aakash Khepar

Screened

Mid-level Full-Stack AI Engineer specializing in agentic AI systems

Tempe, AZ4y exp

“AI/full-stack builder with hands-on experience shipping healthcare, career-tech, nonprofit, and fintech products, spanning speech AI, browser extensions, agentic RAG systems, and enterprise ML monitoring. Stands out for combining strong technical depth with measurable outcomes, including reducing clinical call WER from 26% to 3%, building safe tool-using agents with rollback/RBAC, and delivering zero-to-one multi-tenant platform features in ambiguous environments.”

“Backend/ML engineer who built production LLM-enabled systems at PRGX, including an interpretable contract opportunity scoring engine (Bradley-Terry pairwise ranking) that reached 0.82 weighted Spearman agreement with SME auditors and was integrated into workflow. Also built a Duke student advisor chatbot and hardened it for real-world reliability/security with schema-driven tool calling, normalization, and off-domain defenses; led staged production rollouts with shadow testing and achieved 0.90 F1 on a new extraction field before shipping.”

“Backend engineer who has led major platform evolution to cloud-native microservices (Spring Boot on AWS with Terraform) and built scalable, secure FastAPI APIs. Demonstrates strong production rigor with metric-driven validation, canary/phased rollouts, and incremental migrations using shadow traffic/feature flags/parallel writes—achieving faster deployments, fewer incidents, and zero-downtime traffic spikes and migrations.”

Allan Farinas

Screened

Senior Full-Stack Software Engineer specializing in Python and AWS

West Covina, CA11y exp

“Backend/data engineer who has built production Python microservices (FastAPI) and AWS-native platforms for event ingestion and analytics, combining ECS/Fargate + Lambda with CloudFormation-driven environments and strong secrets/IAM practices. Experienced modernizing legacy logic with parallel-run parity validation and safe phased cutovers, and has demonstrated measurable SQL tuning wins (20–30s down to 1–2s) plus incident ownership in Glue/Step Functions ETL pipelines.”

Sragvi Vadali

Screened

Junior Software Engineer specializing in AI/ML and real-time systems

2y exp

“Backend/AI engineer who built a real-time vector database system for high-frequency financial data using Kafka/Flink on Kubernetes, achieving sub-100ms similarity search at 10k+ concurrent load and resolving tricky duplication issues with idempotency/versioning. Also shipped an end-to-end LLM-based travel itinerary feature (profiling + prompt workflows + APIs) with a focus on quality consistency and low latency.”

Samatha Amsala

Screened

Mid-level Data Engineer specializing in cloud data warehousing and analytics

Omaha, NE6y exp

“Data engineer at American Express who owned end-to-end pipelines for transaction and customer data used in finance reporting and risk analytics, processing ~5–8M records/day. Built Airflow-orchestrated ingestion (including external APIs/web sources) with strong data quality controls, monitoring/alerts, and resilient backfill/retry patterns, and also shipped a versioned REST API serving aggregated metrics to analytics teams.”

Satwik Alla

Screened

Mid-level Full-Stack Software Engineer specializing in scalable APIs and real-time AI apps

United States of America3y exp

“Lead software engineer (3+ years) who built and scaled an AI product backend at Cosmo AGI from the ground up using FastAPI/Postgres/Redis/vector DB, targeting sub-200ms latency and supporting 1000+ active users. Strong in production-grade security and observability (OAuth/JWT, RBAC, Postgres RLS, Prometheus/Sentry), plus DevOps automation (Docker, GitHub Actions, blue-green deploys) with measurable impact on uptime, incidents, engagement, and deployment speed.”

SaiTeasmitha Kaja

Screened

Mid-level Full-Stack Software Engineer specializing in Java/Spring Boot and cloud microservices

Houston, TX4y exp

“Backend-focused Python/Flask engineer who has built authentication/profile services with clean modular architecture (blueprints + service layer) and tuned SQLAlchemy/Postgres for scale using indexing, query rewrites, and pagination. Has production-style integration experience for AI/ML via TensorFlow Serving and OpenAI APIs (batching, rate limiting, caching), plus multi-tenant data isolation and high-throughput background processing with Celery/Redis and idempotent jobs.”