Vetted Amazon RDS Professionals

“Healthcare analytics professional with hands-on experience turning messy claims, eligibility, and utilization data into validated BI-ready models using SQL and Python. They combine strong data engineering and KPI design skills with stakeholder-facing delivery, including Power BI prototyping, retention metric operationalization, and analyses that supported care management interventions and cost-control decisions.”

“Backend-leaning full-stack engineer who builds and operates Spring Boot microservices with React/TypeScript frontends, using Kafka/RabbitMQ for event-driven workflows. Created an internal ops dashboard for Support/SRE with tracing, alert correlation, and self-serve actions, improving MTTR and reducing escalations while maintaining regulatory-grade reliability and security.”

“Backend/data engineer who built an enterprise LLM assistant (AI Genie) at Broadband Insights using a LangChain + GPT-4 + Pinecone RAG pipeline to automate broadband analytics reporting. Developed Python/Dagster ETL processing 10M+ records/day and improved data freshness by 60%, with production-grade scalability patterns (async workers, containerized microservices, Kubernetes) and strong multi-tenant isolation practices.”

“Full-stack engineer who built an email/SMS marketing platform from the ground up using PHP (Yii2/Laravel) and JS (jQuery/Vue components), including campaign reporting, A/B testing, and extensive ESP/SMS integrations (Mailgun/Mailjet/Twilio plus AWS SES/SNS). Notably scaled the system for very large contact ingestion by migrating from MySQL to ClickHouse and implemented reliability measures like retries, logging, and rate limiting.”

“Backend-focused Python engineer who owned high-traffic internal services end-to-end (FastAPI/Django) including REST/GraphQL APIs, PostgreSQL optimization, async task processing via SQS, and full CI/CD. Strong Kubernetes-on-EKS and GitOps (ArgoCD + Helm) experience, plus Kafka real-time streaming work and phased cloud-to-on-prem migration support.”

Pravelliika Chirivella

Screened

Mid-level Full-Stack Developer specializing in Django/React and FinTech automation

New York, NY3y exp

“Product-minded full-stack engineer who owns customer-facing products end-to-end and iterates quickly using MVP validation, feature flags, automated testing, and staged rollouts. Has built TypeScript/React systems with modular backends and designed microservices with async messaging (RabbitMQ), handling scale issues like ordering, retries, and idempotency. Also delivered an internal ops automation tool with a self-serve real-time workflow dashboard that reduced errors and drove rapid adoption.”

Tanisha Pradeep Bhola

Screened

Mid-level Software Development Engineer specializing in backend, cloud, and microservices

Dayton, Ohio4y exp

“Accenture engineer with hands-on experience taking an NLP sentiment analysis system from prototype to production, emphasizing robustness to noisy data, scalability, and observability (dashboards for latency/error/throughput). Also supports customer-facing teams with demos and PoCs, translating client requirements into secure, scalable architectures and troubleshooting LLM/agent workflows via logs and step-level traces.”

Yang Qi

Screened

Mid-level Full-Stack Software Engineer specializing in AI platforms and data visualization

Cambridge, MA3y exp

“Full-stack engineer with healthcare/bioinformatics experience who built a real-time genomic data analysis and 2D visualization feature (React/TypeScript + D3, FastAPI) at University of Utah Health, deploying on AWS ECS Fargate with monitoring and measuring engagement via Google Analytics. Also built AWS Lambda-based ETL pipelines for lab data ingestion using pandas/NumPy with reliability patterns (idempotency, retries, CloudWatch alerting) and drove maintainability improvements through shared component libraries and React hooks.”

Sai Srujan Vemula

Screened

Mid-level Full-Stack Developer specializing in Java/Spring Boot and React on AWS

CT, USA3y exp

“Full-stack engineer with enterprise experience at Meta System and DXC, owning end-to-end delivery of a shipment visibility portal (React UI in Liferay DXP + Java/Spring Boot REST APIs) with Dockerized deployments and automated test coverage. Has hands-on AWS work across EC2/Lambda/S3 and multiple databases (DynamoDB, RDS, Neptune, DocumentDB), plus built a Python/Flask data migration platform with validation for correctness and repeatability.”

“Senior AI/ML engineer with hands-on experience building production LLM systems in healthcare, including RAG-based clinical question answering and end-to-end MLOps on Vertex AI and Kubernetes. They combine strong platform engineering with applied GenAI work, citing a 35% improvement in factual accuracy and a 30% boost in internal team productivity through modular Python services and CI/CD.”

Sai Prudhivi

Screened

Mid Software Engineer specializing in full-stack microservices and cloud platforms

New York, NY4y exp

“Backend-focused engineer with experience building high-volume policy management and enterprise pricing systems, including Django/FastAPI/Flask services, Kafka-based async workflows, and Prometheus/Grafana observability. While they have not yet shipped a customer-facing AI agent or production LLM integration, they bring strong cloud, API, reliability, and scalable system design fundamentals that translate well to responsible AI infrastructure work.”

“Backend/platform engineer with strong ownership of production systems, including a full Azure migration from a VM-based monolith to a containerized, event-driven microservices architecture. They combine cloud infrastructure, LLM/RAG optimization, and pragmatic stakeholder management, with measurable wins including 90% infra cost reduction, faster deployments, and significantly improved latency and token efficiency.”

Sasi Kanduri

Screened

Senior Full-Stack Software Engineer specializing in backend systems and workflow platforms

Sacramento, CA7y exp

“Full-stack engineer with strong React and Python backend depth who has owned complex analytical products end-to-end, from performant UIs to FastAPI services, SQLAlchemy data models, Redis caching, and production observability. Particularly compelling is their 0→1 automation work in the water systems domain, where they built Airflow- and LLM-powered workflows that reduced manual notification and correction work by 90%.”

“Backend engineer with fintech/AI startup experience who built an Azure serverless, event-driven pipeline for large-scale crypto sentiment analysis and semantic search (OCR/NLP to vector search) and integrated LLM + blockchain data for predictive insights. Demonstrated measurable impact (25% lower retrieval latency, 10% fewer data errors, 15% higher engagement) and has led safe microservices migrations with strong security and reliability practices.”

“AI Engineer at Humanitarian AI who has built and productionized both a LangGraph-based multi-agent workflow system and a RAG pipeline (OpenAI embeddings + vector DB) with rigorous evaluation/guardrails. Reports strong measurable impact (60% faster workflow delivery, 40% fewer incidents, 70% reduced research time) and has prior enterprise modernization experience at Infosys migrating ETL to microservices with zero production incidents.”

“Backend/data engineer with strong production experience across Python microservices (FastAPI) and AWS serverless/data platforms (Lambda, API Gateway, Glue, Redshift). Demonstrates reliability and incident ownership (rate limits, retries/circuit breakers, monitoring) and has delivered measurable SQL performance gains (12–15s to <800ms, ~60% CPU reduction). Seeking fully remote work and not open to relocation/onsite meetings.”

“Built a production "Mini RAG Assistant" for internal document Q&A, focusing on grounded answers (anti-hallucination), retrieval quality, and latency/cost optimization. Uses LangChain/LangGraph for orchestration and applies a metrics-driven evaluation loop (including reranking and semantic chunking improvements) while collaborating closely with product stakeholders.”

“Engineer with experience in regulated healthcare and financial systems, including a United Health healthcare service migration to AWS. Built documentation-as-code for CI/CD (Jenkins/Docker/Kubernetes/Terraform + GitHub Actions) that accelerated release cycles from 3 weeks to 4 days and tied security configuration (Spring Security/OAuth2/JWT) directly to HIPAA/GDPR compliance. Strong in observability-led incident response (ELK/Prometheus/Grafana) and performance tuning (PostgreSQL, async processing), citing MTTR reduction from 3 hours to 50 minutes and support for 250K+ concurrent users.”

“Full-stack engineer focused on data-heavy platforms, building Spring Boot microservices and Angular/React dashboards end-to-end. Has hands-on experience improving large-scale API and UI performance (including cutting 8–10s response times) and ensuring cross-service consistency using Kafka, idempotent consumers, and strong validation/transaction patterns on AWS with CI/CD and observability (Prometheus/ELK).”

“Full-stack AI engineer who built Skillmatch AI, an LLM/RAG-based job matching platform using FastAPI microservices, Airflow-orchestrated async pipelines, and Pinecone vector search (sub-second retrieval across 50k+ vectors) deployed on GCP with autoscaling. Also partnered directly with a cancer researcher to automate SEER + PubMed-driven report generation via an AI pipeline, emphasizing rapid prototyping and outcome-focused communication.”

“Founding engineer with strong end-to-end product delivery across IoT + mobile + serverless cloud: built firmware for a Bluetooth-connected device (ESP32), a native Swift iOS app, and an AWS serverless backend (API Gateway/Lambda/SQS/SNS/DynamoDB) including payments via Stripe. Also shipped a separate startup product in 6 months: a React visual tool that generated HTTP/REST APIs with a Django backend, admin panel, and a code-generating CLI.”

“Backend developer (recent co-op at Ticker) building and architecting financial backend services with near real-time data needs, including third-party API integrations. Improved performance and reliability via Redis caching (tiered refresh + TTL) and PostgreSQL query tuning (EXPLAIN ANALYZE + composite indexes), and has exposure to AI-agent/RAG concepts for validating stock-market information against trusted sources.”

Raghavendra Dubey

Screened

Mid-level Software Engineer specializing in Java microservices and cloud-native systems

CA, USA5y exp

“Enterprise workflow/product engineer (DXC) who owned a customer-facing workflow application for 500+ users and improved performance ~30% through API/SQL optimization, caching, and CI/CD-backed iteration. Experienced designing React/TypeScript + Java/Spring Boot systems and operating microservices with RabbitMQ/Kafka-style messaging, emphasizing reliability via DLQs, backpressure, and strong observability. Also built an internal automation dashboard adopted by support/ops teams to cut manual work and reduce SLA misses.”