Pre-screened and vetted.
Mid-level Full-Stack Software Engineer specializing in scalable APIs and real-time AI apps
“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.”
Mid-level AI/ML Engineer specializing in LLMs, RAG, and MLOps on AWS
“LLM engineer who built a production document intelligence/RAG pipeline to extract structured data from thousands of unstructured PDFs, cutting manual review time by 60%. Experienced with LangChain and Airflow orchestration plus rigorous evaluation (labeled datasets, prompt testing, HITL review, monitoring) to improve accuracy and reduce hallucinations while partnering closely with non-technical operations stakeholders.”
Mid-Level Full-Stack .NET Developer specializing in cloud microservices and data pipelines
“Backend/data engineer with experience at Citi and Elevance Health, building end-to-end pipelines and data services in regulated, high-volume environments. They combine Python, SQL, .NET, Azure Functions, and strong observability/reliability patterns to improve processing speed, reduce manual effort, and maintain high uptime across financial and healthcare data platforms.”
Mid Software Engineer specializing in distributed cloud-native backend systems
“Backend/AI workflow engineer who built production-grade orchestration systems for hardware security verification at Silicon Assurance (Nextflow/Python/Postgres) and a multi-agent LLM-driven regulatory code checking system at the University of Florida. Emphasizes reliability: strict plan/execute/verify boundaries, queue-based isolation, and strong observability/auditability with Prometheus/Grafana and persisted prompts/tool calls.”
Senior Software Engineer specializing in backend systems and game platform engineering
“Unity/C# game engineer with about 3 years of experience who owned a high-impact runtime content delivery platform at Zynga/Singa powering LiveOps releases for roughly two years. Their work cut app size by 35-40%, removed a 25K daily activator drop on release days, improved load times by 25%, and supported a feature that drove 10% quarterly revenue growth.”
Senior Full-Stack Developer specializing in scalable web platforms and automation
“Backend/full-stack engineer focused on TypeScript/Node.js systems, with hands-on ownership of a real-time telemetry and dashboard platform built on Kafka, Debezium, PostgreSQL, and GraphQL. Stands out for combining event-driven architecture, correctness/idempotency patterns, strong observability, multi-tenant security, and developer-friendly API design in production environments.”
Junior Software Engineer specializing in full-stack web development
“Built a Flask-based web application for NCAA Men's gymnastics and also worked on a survey-question collection and normalization project for UC Berkeley's Cameron Institute. Shows a clear reliability mindset through validation, testing, logging, and error handling, and is comfortable turning ambiguous, messy data workflows into stable applications.”
Mid-level AI/ML Engineer specializing in FinTech risk and fraud systems
“Senior AI/ML engineer focused on production LLM systems, combining RAG, fine-tuning, distributed training, and AI safety to ship scalable real-time moderation and conversational AI platforms. Stands out for pairing deep AWS/Kubernetes MLOps expertise with measurable impact: 40% lower latency/cost, 30-50% fewer hallucinations, and major reliability gains through observability and automation.”
Mid-level AI/ML Engineer specializing in GenAI, RAG, and healthcare ML
“Built an end-to-end GenAI/RAG platform for financial compliance and research at BlackRock, focused on safe, auditable answers in a highly regulated environment. Combines strong LLM engineering depth with production platform skills and delivered clear business impact, including reducing research/compliance turnaround from hours to seconds, improving retrieval relevance by 22%, and cutting inference costs by 75%.”
Mid-level Software Development Engineer specializing in cloud-native AI/ML systems
“AI/ML-focused engineer with practical experience building RAG-based and multi-agent systems, including architectures for retrieval, reasoning, context processing, and response generation. Stands out for combining LLM productivity gains with disciplined software engineering practices like validation, monitoring, and reproducibility.”
Mid-level Full-Stack Software Engineer specializing in API and data-driven applications
“Full-stack engineer with internship experience at Sports Excitement and AI systems work at the University of Florida, combining React/TypeScript, Node.js, and PostgreSQL with applied AI workflow tooling. Stands out for shipping measurable product improvements—30% faster pagination and 40% higher engagement—and for building observability, eval, and human-review layers around AI-assisted data extraction systems.”
Senior Technical Project Manager specializing in data, systems, and FinTech delivery
“Enterprise implementation and modernization leader with 10+ years across JP Morgan, StoneX, and Majesco, delivering complex B2B/SaaS programs in highly regulated insurance and financial services environments. Has progressed from project coordination into full program ownership, managing $5M+ initiatives and portfolios of 4-6 concurrent enterprise implementations with executive-facing governance.”
Mid-level Full-Stack Engineer specializing in FinTech and cloud-native systems
“Full-stack engineer with production experience building AI-powered search and automation systems at JPMorgan Chase and customer-facing product features at Wayfair. Stands out for combining React frontend work with backend microservices, RAG/LangChain AI integration, and cloud-scale performance tuning, including a support chatbot that reduced ticket resolution time by 35%.”
Senior Full-Stack/Backend Software Engineer specializing in cloud-native automation and microservices
“Backend/data engineer with strong AWS production experience across containers (ECS) and serverless (API Gateway/Lambda/SQS), plus Glue-based ETL to Parquet for Athena/Redshift. Demonstrates hands-on reliability and security depth (Cognito OAuth2/JWT with JWKS rotation, idempotency/DLQs, monitoring) and measurable performance wins (Redis caching + query tuning), along with legacy-to-services modernization using parallel-run parity and feature-flagged cutovers.”
Mid-level Full-Stack Software Engineer specializing in cloud-native web applications
“Backend engineer with hands-on experience scaling a Python/Flask incident-logging platform processing thousands of daily logs. Strong in performance tuning (PostgreSQL/SQLAlchemy query optimization, partitioning, summary tables) and reliability patterns (Redis caching, Celery background workers, Docker + Jenkins CI/CD), with some multi-tenant data isolation experience via separate DBs/schemas.”
Mid-level Full-Stack & GenAI Engineer specializing in RAG and LLM applications
“Software engineer working on an e-commerce platform, currently building a RAG-based recommendation system with a team new to the technology. Has delivered an end-to-end React/TypeScript website for a local car dealer and built an internal "encryption as a service" tool to secure sensitive data across repositories and through release/UAT, with experience debugging microservices integration issues.”
Junior Machine Learning Engineer specializing in multimodal AI and audio deepfakes detection
“Internship experience building production-oriented AI systems, including a real-time voice scam/spoof detector (RawNet + AASIST) hardened for noisy audio via aggressive augmentation and Zoom-based noise simulation, evaluated with EER on clean and wild datasets. Also built an LLM-driven UI automation agent using Playwright for apps like Linear/Notion with modular tool design, unit tests, and replayable scripted scenarios, and has AWS Step Functions experience orchestrating Lambda/Cognito workflows.”
Mid-Level Cloud/Software Engineer specializing in AWS and Salesforce integrations
“Customer-facing technical professional who designs solution architecture and builds PoCs for regulated customers, iterating via biweekly demos and direct feedback to reach production-ready implementations. Regularly delivers technical demos (~2/month for nearly a year) and partners with sales/customer-facing teams by refining technical implementations until they match customer requirements.”
Mid-level AI/ML Engineer specializing in LLMs, RAG, and MLOps
“Red Hat ML/LLM engineer who designed and deployed a production LLM-powered customer support automation system using RAG, improving latency by 30% via PEFT and vector search optimization. Built security and governance into retrieval (access-level filtering, encrypted Pinecone/ChromaDB) and delivered SHAP-based explainability via a dashboard for non-technical stakeholders. Experienced orchestrating distributed ML/RAG pipelines across AWS SageMaker and OpenShift with Airflow/Prefect, plus multi-agent workflows using CrewAI and LangGraph.”
Intern Software Engineer specializing in backend systems, cloud infrastructure, and ML/LLM tooling
“Infrastructure-leaning engineer who has built real-time ML systems end-to-end: a Jetson-deployed adaptive Whisper ASR service (Flask + WebSockets, React/TS UI) and a high-throughput Postgres schema for live transcription. Also delivered customer-facing AI billing/OCR improvements for a dental startup (Dentite), boosting OCR performance by 38%, and has experience instrumenting open-source ML deployment stacks to add infrastructure visibility.”
Mid-level Full-Stack Developer specializing in cloud microservices and internal tooling
“LLM/RAG engineer who has shipped production systems in high-stakes domains (fraud analytics at Mastercard and security compliance as a CI/CD gate). Strong focus on reliability: hybrid retrieval for latency, citation-backed outputs for trust, and code-driven eval/regression pipelines using golden datasets. Also built scalable OCR-based ingestion for messy classroom artifacts (handwriting, PDFs, whiteboard photos) using Go/Python and cloud services.”
Senior QA Lead specializing in test automation and live-service platform quality
“QA/automation engineer with experience at Riot Games’ player platform, owning E2E automation for mission-critical authentication/account flows using Playwright/JavaScript plus API automation. Built CI merge gates and nightly verification with Slack reporting, and repeatedly caught backend-driven session/authorization regressions before production. Known for stabilizing flaky UI tests via selector strategy and network intercepts, and for influencing design early with testability hooks and telemetry.”
Junior Software Engineer specializing in data engineering and LLM applications
“Computer science engineer and master’s graduate who independently built a mechatronics-heavy capstone prototype: a smartphone concept for deafblind users using micro-actuator arrays for braille reading. Also has platform engineering experience at Quantiphi, deploying webhooks to Kubernetes and implementing GitOps-based CI/CD using AWS CodeCommit/CodeBuild and ECR.”
Mid-level Quality Assurance Engineer specializing in AI/ML and Apple ecosystem testing
“QA automation engineer with end-to-end ownership of a regression suite for a warehouse loan management platform (.NET/Angular), using Selenium (Java/Cucumber/POM) and Cypress. Improved suite stability and expanded risk-based coverage (DB/API/SQL, RBAC approval workflows), catching critical financial defects like EMI calculation errors and cutting regression effort by ~50% while gating releases via GitLab CI/CD with actionable Slack reporting.”