Pre-screened and vetted.
Mid-Level Full-Stack Software Engineer specializing in cloud-native data platforms and AI apps
“Software engineer who has owned customer-facing/internal platforms end-to-end, emphasizing fast iteration through small releases backed by monitoring and rollback safety. Built SurveyAI with reusable React/TypeScript components and a stateless Node.js REST backend with clear API contracts/validation, and created an internal Airflow + AWS Lambda automation tool integrated with Slack alerts to reduce manual work and improve response time.”
Senior .NET Full-Stack Developer specializing in cloud, IoT messaging, and real-time web apps
“Full-stack engineer who owns customer-facing web products end-to-end (React/TypeScript + Node.js), shipping frequent releases with strong testing, staged deploys, and production monitoring. Improved a key user flow by batching backend calls and simplifying frontend rendering, driving ~30% faster load times and ~30% higher completion rates. Also built an ops monitoring dashboard using ELK + Prometheus/Grafana that cut incident response time by 40% and has hands-on microservices messaging experience (RabbitMQ/Kafka, idempotency, DLQs).”
Junior QA Automation Engineer specializing in Playwright E2E and API testing
“QA automation-focused engineer who hardens production CI/CD by integrating and stabilizing end-to-end automated tests (tackling async UI flakiness, resilient assertions/selectors, and controlled test data). Demonstrates strong cross-layer troubleshooting by correlating logs and system metrics to resolve intermittent service reachability, then adding monitoring/alerts and documentation. Also partners directly with operators to improve real-world workflows by enhancing validation logic and error messaging.”
Mid-level Machine Learning Engineer specializing in cloud, governance automation, and distributed systems
“Governance engineer intern at GSK who built policy-as-code automation using Open Policy Agent/Rego integrated into GitHub CI/CD and Terraform workflows. Also built and shipped a voice-enabled expense tracking app using speech-to-text + LLM structured extraction with strong validation, retries, and semantic guardrails, and designed the supporting PostgreSQL data model with performance-focused indexing.”
Mid-level Site Reliability Engineer specializing in AWS cloud and AI-driven backend systems
“Backend/AI engineer in healthcare/insurance (mentions Cigna) who has shipped production systems spanning high-reliability APIs, async job architectures (Celery), and LLM/RAG features. Built an LLM document assistant with Terraform-managed AWS infra, semantic search retrieval, and strict permissioning/audit logs, and designed an automated prior-authorization workflow with human-in-the-loop escalation and compliance-driven thresholds.”
Junior Software Engineer specializing in full-stack, AI/ML systems, and game development
“Full-stack engineer (React/TypeScript + Bun/Node-like backend) who recently rebuilt a terminal-based chat UI, implementing custom Markdown lex/parse/render and a typewriter-style streaming renderer while optimizing React DOM growth for ~50% faster performance. Has startup experience making high-ownership decisions under ambiguity and rapidly integrating multiple external AI/tooling services (5–6 in a week) with fallback strategies for flaky dependencies.”
Junior Software Engineer specializing in agentic automation and AI platforms
“Backend-leaning founding/early engineer who built automation platforms end-to-end: FastAPI/Python services integrated with a Next.js/TypeScript frontend, including a production VNC streaming URL endpoint for cloud-instance desktop viewing. Also designed core Postgres user/workflow data models and built an agentic orchestration system with LangChain/LangGraph (sub-agents, validators, pause/resume), plus made scalability tradeoffs like S3 pre-signed uploads to keep microservices responsive.”
Mid-level Implementation Engineer specializing in enterprise integrations and IAM/PAM
“Data/ML engineer with end-to-end ownership of donor-data deployments for a university foundation, delivering major performance and data-quality gains (500K+ records; 24h to 6h processing; duplicates 5% to 1%). Has put an LLM-assisted enrichment workflow into production with retrieval-grounded business rules, versioned outputs for traceability, and strong operational rigor around validation, logging, and CI/CD.”
“Early-career full-stack developer who has independently built a job application platform with Apollo-based backend APIs, schema design, CRUD operations, and search/filter functionality. Also experimented with AI integration through an image-generation app, and is candid about still growing in production-scale engineering rigor.”
Mid-level Software Engineer specializing in AI/ML and full-stack development
“Backend Java engineer with strong platform/DevOps experience: modernized an insurance claims legacy monolith into DDD-aligned microservices, deployed containerized services on Kubernetes with Jenkins CI/CD and static analysis gates, and implemented GitOps using ArgoCD. Also led major AWS migration planning with dependency mapping and network monitoring to uncover hidden dependencies, and built Kafka-based real-time event streaming with schema-registry-driven evolution.”
Mid-level Java Full-Stack Developer specializing in scalable web applications
“Full-stack Java developer from Cognizant who built a real-time transaction monitoring and tracking platform for operations and customer visibility. Stands out for combining Spring Boot, React/TypeScript, Kafka, and CI/CD tooling to ship near real-time dashboards, while also working directly with users to refine requirements and improve performance in high-volume transaction environments.”
Senior Product Leader specializing in enterprise SaaS, telecom, and e-commerce
“Product leader focused on transforming legacy white-label personal cloud platforms into AI-native consumer experiences at global telecom scale. They led the launch of ML-powered features across brands like AT&T, Verizon, and SoftBank, drove ~25% MAU growth, and paired strong UX judgment with deep technical fluency in AI infrastructure, rollout governance, and cost optimization.”
Mid-level AI/ML Engineer specializing in RAG systems and Python cloud backends
“Frontend engineer with hands-on experience building AI-powered document search and analytics products, including RAG-based knowledge retrieval interfaces with citations, filters, and document previews. Stands out for combining React/TypeScript architecture with production performance tuning using profiling tools, memoization, lazy loading, and debounced data flows to keep complex, document-heavy UIs responsive.”
Mid-level Software Engineer specializing in full-stack cloud-native applications
“Full-stack engineer with cloud and GenAI experience who has owned production features end-to-end, including a reporting dashboard optimized from 14s to 5s using query/API refactoring and monitored via AWS CloudWatch. Also productionized an OpenAI-powered chatbot using LangChain with prompt design, guardrails, and evaluation via production logs and user feedback, and has led incremental legacy-to-microservices modernization with parallel run to avoid regressions.”
Senior Full-Stack Engineer specializing in cloud-native and AI-powered systems
“Full-stack engineer with experience spanning React/TypeScript frontends, Node.js backend services, and production systems on AWS. They’ve built real-time, event-driven inventory workflows using PostgreSQL, Redis, RabbitMQ, and Keycloak, and also drove a multi-agent LangGraph architecture for a self-healing systems project evaluated on simulated Kubernetes outages.”
Junior Software Engineer specializing in AI/ML, data pipelines, and cloud APIs
“Hands-on AI/LLM practitioner who built a RAG-based customer support chatbot and tackled production issues like data chunking complexity and response-time lag. Uses techniques such as overlapping chunks, semantic search, context engineering, and query routing, and has experience presenting technical demos/workshops to developer audiences.”
Mid-Level AI Backend Engineer specializing in Python, LLM/RAG, and healthcare/insurance platforms
“AI Backend Engineer in MetLife’s claims technology group who built and deployed a production LLM-based decision support system that helps claim adjusters quickly find relevant policy rules from long PDFs and historical notes. Designed it as multiple production-grade services with retrieval-first guardrails, continuous validation, and Airflow-orchestrated pipelines for ingestion, embeddings, and vector index updates to keep the system reliable as policies and data evolve.”
Mid-Level Full-Stack Software Engineer specializing in cloud-native and mobile applications
“LLM-focused engineer with end-to-end experience shipping an OpenAI-powered edtech teacher assistant into production, using Humanloop-driven prompt iteration, rigorous observability (Datadog), and A/B testing tied to real learning metrics (25% comprehension lift). Also led adoption-driving technical demos at SiriusXM (event-driven AWS Lambda/Kotlin/CDK pipeline cutting processing from 24 hours to seconds) and partnered with sales at Spresso.ai to close eCommerce SDK deals and boost activation from 40% to 85%.”
Mid-level .NET Backend Developer specializing in secure APIs and enterprise integrations
“Built and owned UPS tracking/reporting and operations workflow dashboards, delivering customer-facing APIs and real-time React/TypeScript UIs backed by .NET Core. Experienced in high-volume microservices using IBM MQ/Azure Service Bus with strong reliability patterns (idempotency, retries, DLQ) and Azure-based observability, plus performance tuning across frontend and SQL-backed services.”
Mid-level Full-Stack Software Engineer specializing in Java/Spring Boot, React, and cloud
“Backend/platform engineer who built real-time connected-vehicle telemetry analytics at Subaru, spanning Kafka streaming, Python/FastAPI ETL, and low-latency WebSocket delivery (minutes to <2s). Strong Kubernetes + GitOps practitioner across AWS EKS and Azure AKS (Helm, ArgoCD, Jenkins/GitLab) and has led major on-prem-to-cloud migrations for financial microservices using Terraform and AWS DMS with measurable cost and reliability gains.”
Mid-level Software Engineer specializing in cloud-native data pipelines and ML platforms
“Backend engineer who has owned end-to-end delivery of Python/FastAPI microservices for real-time data processing and alerting, including performance tuning (Postgres optimization, caching, async processing). Strong DevOps/GitOps background: Docker + Kubernetes deployments with GitHub Actions CI/CD and ArgoCD-driven GitOps, plus experience supporting phased on-prem to AWS migrations and building Kafka-based streaming pipelines.”
Mid-level Full-Stack/Backend Java Developer specializing in IAM and microservices
“Full-stack Java developer (~4 years) who built a telecom asset management system end-to-end with React and Spring Boot, and led/participated heavily in migrating it from a monolith to Spring Cloud-based microservices. Experienced with high-volume, data-driven workloads using Kafka (partitioning, batching, resilient consumers) and production observability via centralized logging with ELK and Splunk.”
Mid-level Full-Stack Engineer specializing in AWS serverless and secure web applications
“JavaScript full-stack engineer with experience at EY building secure, cloud-ready React/Node.js applications on AWS and currently at startup Juego Juegos owning the AWS backend and CI/CD via AWS Amplify. Demonstrated impact through performance tuning of a React analytics dashboard (reduced initial load time ~20%) and resolving real payment failures by debugging Stripe 3DS flows and updating AWS Lambda plus frontend error handling.”
Mid-level Full-Stack Developer specializing in Java, Spring Boot, and cloud-native web apps
“Full-stack engineer with strong React/TypeScript and Java Spring Boot microservices experience who has built end-to-end task management and real-time, data-intensive dashboards. Demonstrates practical depth in security (JWT, RBAC, token refresh), performance optimization (indexing/aggregations, virtualization, caching), and cloud deployment (AWS, Docker, Jenkins, Kubernetes).”