Vetted Structured Logging Professionals

Pre-screened and vetted.

SC

Mid-level Full-Stack Software Engineer specializing in AI-powered web products

San Jose, CA4y exp
Surge AinaUniversity of Illinois Chicago

Early engineer at a fast-growing startup who owned an AI-powered portfolio/site generation workflow end-to-end (frontend in Next.js App Router/TypeScript through backend orchestration). Emphasizes server-first security/performance (Server Components/Actions, revalidation), and production hardening with validation, caching, observability, retries/idempotency, and CI/E2E testing.

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KL

Mid-level Full-Stack Software Engineer specializing in enterprise web apps and real-time dashboards

Stanton, TN6y exp
SK Battery AmericaUniversity of Mississippi

Backend/full-stack engineer from Foxconn Industrial Internet who led development of a production TypeScript/Node.js facility monitoring platform delivering near real-time manufacturing metrics (e.g., downtime and OEE) using MySQL + InfluxDB and a React dashboard. Demonstrates strong production operations mindset with queue-based workers, idempotency/DLQ patterns, structured observability, and automated Docker + GitLab CI/CD deployments.

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AB

Senior Data & Platform Engineer specializing in cloud-native streaming and distributed systems

USA10y exp
JPMorgan ChaseNew York Institute of Technology

Financial data engineer who has built and operated high-volume batch + streaming pipelines (200–300 GB/day; 5–10k events/sec) using AWS, Spark/Delta, Airflow, Kafka, and Snowflake, with strong emphasis on data quality and reliability. Demonstrated measurable impact via 99.9% SLA adherence, major reductions in bad records/nulls, MTTR improvements, and significant latency/runtime/query performance gains; also built a distributed web-scraping system processing 5–10M records/day with anti-bot and schema-drift defenses.

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KR

Mid-Level Backend Engineer specializing in SaaS, FinTech, and AI document intelligence

San Francisco, CA3y exp
IntraEdgeNYU

Full-stack engineer who built an AI-driven document analysis and processing workflow end-to-end, including large-document ingestion, queued async processing, and low-latency retrieval for user-facing flows. Demonstrated practical performance tuning (moving heavy work off request path, polling, caching) and Postgres optimization validated with EXPLAIN ANALYZE, plus durable workflow resilience via retries and dead-letter queues.

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NP

Neel Patel

Screened

Mid-level Python Backend Engineer specializing in cloud-native systems and AI services

USA4y exp
ComcastUniversity at Buffalo

Backend/AI engineer who has shipped an LLM-powered enterprise support-ticket agent at Comcast, building a production-grade microservices pipeline (FastAPI, SQS, Redis) with strong observability (OpenTelemetry/Splunk/Prometheus/Grafana) and reliability patterns (async, caching, circuit breakers, idempotency). Demonstrated quantified impact at scale—processing 10k+ tickets/day while improving response SLAs and routing accuracy through evaluation and human feedback loops.

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VR

Mid-level Backend/AI Software Developer specializing in data pipelines for FinTech and healthcare

6y exp
TMV InvestmentsWright State University

Data engineer/backend data services builder with end-to-end ownership of production pipelines for a Pfizer client, combining Python/SQL ingestion and transformation with strong data quality controls. Delivered measurable performance gains (~30% faster queries) and improved reliability through monitoring/alerting (Splunk, Prometheus/Grafana), structured logging, and incident response; also built internal REST APIs with versioning and caching and set up GitLab-based CI/CD with containerized deployments.

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Shivani Sharma - Mid-Level Software Engineer specializing in Cloud, DevOps, and MLOps in Boston, MA

Mid-Level Software Engineer specializing in Cloud, DevOps, and MLOps

Boston, MA3y exp
Northeastern UniversityNortheastern University

Built and productionized a recommendation system from notebook prototype into a low-latency, scalable Cloud Run service using Docker, FastAPI, Terraform, CI/CD (GitHub Actions), and MLOps tooling (Vertex AI, MLflow). Experienced diagnosing real-time workflow issues using structured logging/ELK and GCP metrics, including resolving intermittent 504s by fixing unbounded SQL and adding caching. Also partners with sales/customer teams (Wasabi) to deliver tailored demos, troubleshoot, and drive onboarding/adoption.

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Gitesh Sagvekar - Mid-level Full-Stack Developer specializing in cloud-native healthcare applications in USA

Mid-level Full-Stack Developer specializing in cloud-native healthcare applications

USA4y exp
AmgenClark University

Full-stack engineer with recent experience at Amgen building an internal healthcare data validation/transformation and workflow automation service: Python/FastAPI backend with REST APIs plus a React UI, designed around a canonical contract-first model to handle inconsistent upstream data. Operates production systems on AWS (EC2/ELB/S3/CloudFront) with strong focus on observability (structured logs, correlation IDs) and safe CI/CD-driven migrations; also has experience shipping quickly in ambiguous environments at TCS.

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SreeHarsha Kelam - Senior DevOps / Site Reliability Engineer specializing in cloud infrastructure in Atlanta, GA

Senior DevOps / Site Reliability Engineer specializing in cloud infrastructure

Atlanta, GA5y exp
NCR VoyixTrine University

GCP-focused database/platform engineer with hands-on production experience operating Cloud SQL at scale, especially around performance tuning, reliability, and day-2 operations. Has supported migration from a single-instance database setup to a more scalable GCP architecture and built Terraform/Python automation for provisioning and recovery workflows.

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NK

Nikhitha K

Screened

Mid-level Full-Stack Java Developer specializing in cloud-native microservices

Minnesota, MN6y exp
Best BuyUniversity of Central Oklahoma

Full-stack engineer with production experience across React/TypeScript, Node/Express, and Java/Spring Boot, operating containerized systems on AWS (EKS/ECS/EC2/RDS/S3) with strong observability (CloudWatch/Grafana). Notable for fixing a real checkout/order-placement failure end-to-end by adding frontend submission guards and backend idempotency with Redis + Kafka deduplication, then validating impact via technical metrics and business KPIs. Has also built Kafka-based integrations/pipelines with robust retry/backfill/reconciliation patterns in retail and banking contexts.

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SK

Junior Full-Stack Engineer specializing in TypeScript/React, Python, and AWS

Lafayette, Colorado2y exp
MedtronicUniversity of Colorado Boulder

Full-stack engineer who built and owned an end-to-end real-time engineering dashboard for Medtronic robotic surgical systems, streaming high-frequency sensor/kinematic data via Python WebSockets to a React/TypeScript UI. Differentiates through performance/reliability practices (stable core vs experimental layer, observability, caching) and high-impact 3D visualization + session playback that became part of engineers' regular bench-testing workflows.

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VR

Mid-Level Software Engineer specializing in Java/Spring microservices and event-driven systems

Kansas City, MO5y exp
Wells FargoUniversity of Missouri-Kansas City

Software engineer experienced in e-commerce systems, building customer-facing features and internal operations tools with TypeScript/React frontends and Spring Boot microservices. Demonstrated measurable performance wins (order-tracking API improved from ~2s to <700ms) and strong event-driven reliability practices with RabbitMQ (idempotency, DLQs, retry/backoff), including resolving a production queue backlog incident. Built an ops dashboard with real-time cross-service order tracing that became a daily tool for support/ops and reduced escalations to engineering.

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LV

Mid-Level Software Developer specializing in Java/Spring microservices and Salesforce

USA5y exp
Wells FargoUniversity of Maryland, Baltimore County

Backend/AI engineer who built an AI icon-generation SaaS backend (Java/Spring Boot, MongoDB) on AWS, including async job processing with idempotency and S3-based result storage to handle traffic spikes. Also shipped applied AI in finance—an end-to-end fraud detection pipeline with risk scoring—and designed a banking support AI agent with strict guardrails, audit logs, and human-in-the-loop escalation.

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SS

Sai Savaram

Screened

Mid-Level Software Engineer specializing in microservices and cloud-native systems

NJ, USA3y exp
DHLUniversity of Texas at Arlington

Backend-leaning full-stack engineer with logistics domain experience (DHL) who shipped a real-time shipment status update system using Spring Boot + Kafka and a performance-tuned PostgreSQL tracking schema. Also has AWS production operations experience (ECS/Kubernetes, Jenkins CI/CD, Terraform/Ansible) and has handled peak-load incidents end-to-end by tracing Kafka lag to database bottlenecks and resolving via query/index optimization plus scaling.

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MB

Intern Machine Learning & Full-Stack Engineer specializing in computer vision and healthcare AI

India0y exp
Amrita Vishwa VidyapeethamUniversity of Illinois Urbana-Champaign

AI/ML-focused backend engineer who shipped two production systems: PersonaPal (agentic LLM chatbot with RAG, FAISS-based retrieval, and Redis semantic caching) and CervixScan (clinical diagnostics platform with PostgreSQL data modeling and human-in-the-loop safety for low-confidence predictions). Demonstrates strong performance/reliability work (indexed vector search, caching, query optimization to ~200ms) and end-to-end ownership from orchestration design through deployment.

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RA

Mid-level Backend Software Engineer specializing in cloud-native Java microservices (FinTech)

Gainesville, FL4y exp
PrudentialUniversity of Florida

Software engineer with Prudential Financial experience building enterprise Spring Boot microservices for policy/risk assessment, including integrating Python ML models via Flask and hardening services with resiliency patterns. Also led an AWS lift-and-shift modernization during an internship (EC2/ELB/Route53/Auto Scaling) and built a personal diffusion-model text-to-music project using BERT tokens mapped to Mel spectrograms.

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Hiya Kothari - Intern Full-Stack Software Engineer specializing in AI/ML and cloud in San Francisco, CA

Hiya Kothari

Screened

Intern Full-Stack Software Engineer specializing in AI/ML and cloud

San Francisco, CA3y exp
Sparx LabsUC Irvine

Built a Python-based geospatial machine learning backend for PFAS contamination risk mapping, including reproducible feature pipelines, ensemble modeling, and a FastAPI layer for visualization/analysis. Emphasizes data integrity and robustness (CRS/coverage checks, fail-fast validation) and has led safe backend refactors using feature flags, idempotent backfills, and Postgres RLS for secure, queryable results delivery.

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Omkar Tulsidas Parab - Mid-Level Full-Stack Software Engineer specializing in web apps, data pipelines, and ML in San Francisco, CA

Mid-Level Full-Stack Software Engineer specializing in web apps, data pipelines, and ML

San Francisco, CA4y exp
University of FloridaUniversity of Florida

Software engineer who owned an Order Management System end-to-end at Reliance Jio, improving large-table performance via UI virtualization shipped behind feature flags and refined through direct ops-user observation. Also built an OCR automation tool at Piramal Realty using Python/Tesseract with validation and manual correction fallbacks, driving adoption by operations teams. Experienced integrating with Kafka-based microservices and improving observability using structured logging and correlation IDs.

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Saniya Athani - Junior Software Engineer specializing in cloud-native DevOps and GenAI in San Francisco Bay Area, CA

Saniya Athani

Screened

Junior Software Engineer specializing in cloud-native DevOps and GenAI

San Francisco Bay Area, CA2y exp
IpserLabNortheastern University

Cloud-focused engineer with hands-on experience deploying production cloud-native REST APIs on AWS using Pulumi IaC, containerization, and CI/CD, with strong emphasis on secure credential management and operational monitoring via CloudWatch. Also has IoT troubleshooting experience across edge hardware constraints and networking (TLS handshake failures), plus Python-based configurable data-processing tools and customer-facing requirements translation.

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VM

Mid-Level Full-Stack/Backend Engineer specializing in AWS, APIs, and GenAI systems

Los Angeles, CA5y exp
AIRKITCHENZCalifornia State University, Fullerton

Backend engineer who built the core backend for Air Kitchens’ discovery/booking platform on AWS (Node + Python, DynamoDB, SQS/Lambda), optimizing for fast user-facing APIs and scalable async workflows. Introduced an AI matching service with a deterministic pre-filter + LLM ranking approach to balance latency vs quality, and has hands-on experience with production security (JWT/RBAC/RLS), CI/CD, and blue-green, staged migrations from Django to modular services.

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SM

Mid-level Full-Stack Software Developer specializing in cloud-native microservices

WI, USA3y exp
Cardinal HealthAnderson University

Full-stack engineer with enterprise experience at Metasystems Inc. (and Qualcomm) building high-traffic, security-sensitive systems—owned a secure transaction processing module end-to-end using Java/Spring Boot, Python/Django, and React. Strong AWS production operations (EKS/ECS/Lambda/RDS/DynamoDB) with IaC (Terraform/CloudFormation), observability, and reliability patterns; also delivered resilient ETL/integration pipelines with idempotency/retries/backfills and achieved a 50% deployment-time reduction through CI/CD and modular refactoring.

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SC

Mid-level Full-Stack Developer specializing in React/Node, GraphQL, and Databricks lakehouse

Dallas, TX6y exp
Southern Glazer's Wine & SpiritsWebster University

Full-stack engineer currently at Southern Glazer’s who built and owned a real-time commercial finance expense analytics dashboard end-to-end (Next.js App Router + TypeScript), including post-launch monitoring, data quality checks, and stakeholder-driven iteration. Strong data/analytics backend experience (Postgres modeling and Databricks Delta Lake pipelines) with demonstrated performance wins—e.g., cutting a key reconciliation query from 8–12s to <400ms and improving frontend load time ~40% with a 25% bounce-rate drop at Verizon.

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NU

Nikhil Urkude

Screened

Senior Backend Software Engineer specializing in distributed systems and enterprise SaaS

Irving, TX10y exp
PaycomUniversity of Texas at Arlington

Backend/platform engineer with Paycom experience owning a core enterprise compliance feature (certification approval workflow) end-to-end, including live migration behind feature flags and production monitoring. Delivered measurable impact (40% faster workflow completion, major drop in escalations) and also built GraphQL microservices integrating certification workflows into an enterprise AI platform while driving significant API latency reductions (20s to <6s).

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