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Vetted jQuery Professionals
Pre-screened and vetted.
Senior Full-Stack Engineer specializing in Python and AWS-native application development
Director-level Mobile & Full-Stack Software Engineer specializing in Android and cloud-native apps
Senior Data Engineer specializing in AWS-based data pipelines and multi-tenant SaaS
Alexis Abbott
Senior Python Developer specializing in AWS, microservices, and data pipelines
“Backend/data engineer with strong AWS production experience spanning serverless APIs and containerized workers (Lambda, API Gateway, ECS) plus data pipelines (Glue, S3, Athena/Redshift). Has modernized legacy SAS/cron batch systems into Python/AWS with parallel-run parity validation and low-risk cutovers, and has owned ETL incidents end-to-end (CloudWatch detection, backfills, and preventative controls). Targeting $130k–$150k base and strongly prefers remote, with occasional Bethesda onsite acceptable.”
SAI PRASHANTH
Mid-level Full-Stack Software Engineer specializing in cloud-native microservices and FinTech
“Software engineer/product-minded builder who owns customer-facing products end-to-end and ships in 1–2 week increments using CI/CD, automated testing, and feature flags. Built a TypeScript/React/Node platform that cut page load times by 40% and scaled to 3x concurrent users, and designed RabbitMQ-based microservices with Prometheus/Grafana monitoring. Also delivered an internal real-time support analytics dashboard that reduced response times by 30%.”
Malli Karjuna
Mid-Level .NET Full-Stack Developer specializing in cloud-native web applications
“JavaScript engineer with open-source library contribution experience, including diagnosing a validation-related bug, shipping a tested fix, and improving documentation with practical examples and edge-case guidance to reduce repeated community questions. Emphasizes profiling-driven performance work, small safe refactors, and proactive ownership in fast-moving, unstructured teams.”
Shubh Dholakiya
Mid-Level Full-Stack Software Developer specializing in Java/Spring microservices and cloud
“Backend engineer who owned and shipped a campaign analytics API (FastAPI/Postgres/Redis/Celery) with ingestion from Instagram/YouTube, JWT auth, tests, and Docker deployment; improved performance from >1s to <150ms using precomputed aggregates and composite indexes. Experienced with Kubernetes GitOps using GitHub Actions + ArgoCD (zero-downtime rollouts, one-click rollbacks), Prometheus/Grafana observability, hybrid cloud-to-on-prem migrations, and real-time notification streaming via Redis Pub/Sub + WebSockets.”
Mid-level Full-Stack Java Developer specializing in Spring Boot, React/Angular, and AWS
Mid-Level Software Engineer specializing in Azure cloud infrastructure and full-stack development
Mid-Level Full-Stack Software Engineer specializing in microservices and Generative AI
Mid-level Full-Stack Developer specializing in Java/Spring Boot, React/Angular, and cloud microservices
Senior .NET Full-Stack Engineer specializing in enterprise web apps and cloud platforms
Mid-level AI/ML Engineer specializing in cloud-native data pipelines and RAG systems
Senior Full-Stack Engineer specializing in cloud-native platforms, DevOps, and Kubernetes
Mid-level .NET Full-Stack Developer specializing in scalable web applications and APIs
Mid-level Full-Stack Java Developer specializing in FinTech and cloud microservices
Senior Full-Stack Software Engineer specializing in AWS, .NET, and data/telemetry platforms
Senior Software Engineer specializing in robotics, computer vision, and scientific instrumentation
Senior Full-Stack Software Engineer specializing in Python, React, and LLM-powered applications
Priyanka Ramesh
Junior Full-Stack Software Engineer specializing in Java/Spring Boot and React
“Backend engineer (IpserLab) who owned Python services for a production quiz/analytics platform, focusing on reliability and low-latency behavior under peak load. Hands-on with Kubernetes + Docker deployments and GitHub Actions CI/CD in a GitOps-style workflow, including solving configuration drift and enabling fast rollbacks. Also implemented Kafka-based event streaming with idempotent consumers and strong observability (lag tracking, structured logging, alerting).”