Pre-screened and vetted.
Mid-Level Full-Stack Software Engineer specializing in cloud-native microservices and DevSecOps
“Backend-leaning product engineer with DevSecOps depth who has shipped real-time, Kafka-driven data pipelines and AI-enabled customer-facing features to production on AWS. Built a Spring Boot API layer serving real-time predictions at 100K+ requests/day, improving latency by 35% and user task completion by ~25%, and delivered a React/TypeScript dashboard plus a Postgres audit/history model optimized for search and large event volumes.”
Mid-Level Software Engineer specializing in microservices, data pipelines, and FinTech fraud detection
“Backend engineer with PayPal experience owning a high-throughput, low-latency fraud detection pipeline processing billions of transactions/day, integrating LLM-based models into real-time Kafka streams and payment decisioning APIs. Strong Kubernetes + GitOps practitioner (declarative, auditable deployments; autoscaling/probe tuning) with migration experience modernizing legacy systems onto AKS/OpenShift.”
Senior Data Analyst specializing in data pipelines, web scraping, and legal data enrichment
“Data engineer focused on reliable, scalable analytics pipelines and external data collection. Has owned end-to-end pipelines processing 5–10M records/day, serving Snowflake data marts to Power BI/Tableau, and reports ~99% reliability through strong validation/monitoring. Also shipped versioned REST APIs for curated data with query optimization and caching.”
Junior Software Engineer specializing in AI, RAG systems, and backend development
“Built an NYU software engineering capstone called “Smart Cash AI,” a multi-agent LLM-powered web app that curates offline-ready podcasts/articles/videos/news based on user preferences and commute schedules. Architected agent orchestration (discovery/downloader/summarizer), real-time progress via WebSockets, and an ETL normalization layer across RSS/YouTube and other sources with GUID-based deduplication, retries, and failure isolation to keep the system predictable.”
Senior QA Engineer specializing in mobile and web application testing
“Console game QA tester with hands-on experience validating functionality, UI/controls, loading/performance, and payment-related features across multiple console platforms. Works from structured test cases in TestRail, manages daily QA readiness and regression cycles, and escalates issues quickly via Jira bug cards while coordinating prioritization with developers and PMs under tight submission deadlines. ISTQB CTFL certified and interested in high-impact, demanding projects.”
Senior QA Engineer specializing in manual/automation testing for web and mobile products
“QA tester with experience at Tokopedia (major Indonesian e-commerce) handling concurrent web/Android/iOS releases, including regression testing, stakeholder coordination, and full bug-ticket lifecycle management. Has additional PC/mobile game testing exposure (personal/adhoc) and uses AI tools to generate edge test cases and detect bug patterns; interested in taking on heavy, high-impact projects.”
Mid-level Supply Chain Analyst specializing in inventory optimization and demand planning
“Wayfair strategic sourcing/procurement professional who led a major shift from push-based replenishment to a demand-driven pull model, combining SAP IBP/S4HANA planning with supplier renegotiations and performance scorecards. Drove measurable outcomes including $100K annual savings, 98% on-time delivery, and an SAP Fiori + Tableau inventory visibility improvement that cut 1,500 units of waste and saved $150K.”
Mid-level Machine Learning Engineer specializing in NLP, LLMs, and applied research
“New grad SDE (AI/ML) who built and deployed an LLM-based chatbot framework used across technology, military, and banking contexts, focusing on model selection tradeoffs (latency vs accuracy) through prototyping and benchmarking. Also built a multi-agent "eaterybot" using PyAutoGen/AutoGen with a manager agent orchestrating specialized agents, and emphasizes rigorous testing with adversarial/edge-case datasets and hallucination checks.”
Mid-level Java Full-Stack Developer specializing in banking and telecom platforms
“Frontend-focused engineer with experience at T-Mobile and U.S. Bank who maintained a TypeScript utility library (types, tests, build pipeline, and docs) adopted by multiple teams, and improved React workflow performance by refactoring components and optimizing data fetching. Known for pragmatic cross-team support—reproducing issues quickly, shipping well-tested fixes, and managing changes carefully to avoid breaking downstream apps.”
Mid-level AI/ML Engineer specializing in LLM agents, RAG, and ML systems
“At Inertia Systems, built a production LLM-powered ingestion pipeline that converts heterogeneous sources (PDF/JSON/IFC/SQL and financial tables) into standardized text and uses GraphRAG to construct a knowledge graph with verified dependency relationships. Also has hands-on HPC orchestration experience with SLURM, including creating a custom wrapper process manager to improve resource utilization under restrictive scheduling policies.”
Junior AI/Full-Stack Engineer specializing in LLM apps and RAG systems
“AI engineer who built and shipped a production AI document-understanding/search system at Sumeru Inc, including a full RAG + LLMOps evaluation stack (MLflow, DeepEval, RAGAS) deployed on GCP. Also developed LangChain/LangGraph multi-agent workflows for UAV flight-log analysis and has experience presenting AI solutions to non-technical stakeholders and prospect clients to drive POCs.”
Mid-Level Software Engineer specializing in cloud-native microservices and FinTech platforms
“Backend/platform engineer who led an end-to-end Python (FastAPI) transaction analytics microservice for real-time financial monitoring, including SQS ingestion, scoring/aggregation, and low-latency APIs. Strong AWS + Kubernetes/GitOps background (EKS, ArgoCD, Jenkins, ECS/ECR, CloudWatch) with hands-on experience scaling event-driven systems and executing phased on-prem to AWS migrations.”
Mid-level Data Scientist / ML Engineer specializing in secure GenAI and financial compliance
“Built a production "sentinel insight engine" to tame information overload from millions of product reviews and support transcripts, combining Azure OpenAI (GPT-3.5) zero-shot classification with a fine-tuned T5 summarizer to generate weekly actionable product insights. Demonstrated strong MLOps/production engineering by adding drift monitoring with embedding-based detection, integrating REST with legacy SOAP/queue-based CRM via FastAPI middleware, and scaling reliably on Kubernetes with HPA.”
Intern Software Engineer specializing in cloud, big data, and test automation
“Internship experience at Qualitest building and deploying an LLM-powered test automation system that reduced manual test creation and improved efficiency (~40%). Demonstrates strong production engineering for LLM systems (timeouts/retries/monitoring/caching, prompt optimization, batching) and has scaled workflows to 100+ concurrent jobs; also has orchestration experience with AWS Step Functions and Kubernetes.”
“Unity/gameplay engineer (Playtika) who built a state-machine/ECS-driven slot/bonus engine in a client-server setup, focusing on consistent outcomes under latency and highly engaging reward sequences. Also implemented server-authoritative real-time challenges/contests via an event-driven messaging system (SignalR-like) across iOS/Android/WebGL/UWP, and validates impact through retention/session/engagement analytics.”
Mid-level Data Engineer specializing in big data pipelines and real-time streaming
“Data engineer who has owned end-to-end production pipelines processing a few million records/day, using Python/Airflow/SQL/PySpark with Snowflake serving to BI (Power BI). Built resilient external web data collection systems (anti-bot, schema-change detection, backfills) and shipped versioned REST APIs for internal consumers, improving pipeline success rates to 99% through monitoring, retries, and idempotent design.”
Senior QA Manager / QA Lead specializing in automation and Agile delivery across Banking and FinTech
“QA leader with end-to-end ownership of a web-UI automated B2B pricing platform at Cargill, known for using defect trend analytics (Jira/Jira AI) to uncover systemic config/integration risks before UAT/production. Implemented durable CAPA controls (config-change impact assessment gates) and improved release transparency with Copilot-generated Confluence readiness dashboards; cites 15% logistics cost reduction and 60% operational efficacy improvement. Also coordinated cross-shore QA teams across multiple countries with structured cadences and escalation paths.”
Mid-Level Data Engineer specializing in cloud data platforms and governed analytics
“Data engineer with Optum experience building end-to-end healthcare data pipelines for HL7/FHIR, processing millions of records daily across Kafka streaming and Databricks/Spark batch. Strong focus on data quality (schema enforcement/validations), reliability (Airflow monitoring/alerts), and analytics-ready serving in Snowflake powering Power BI/Tableau, with CI/CD via Git and Jenkins.”
Junior Software Engineer specializing in LLMs, ML, and full-stack development
“Built and shipped a production LLM-driven data harmonization/record-matching pipeline for pharmaceutical datasets, combining normalization, embeddings/vector search, and an LLM validation step. Emphasizes production reliability via guardrails, confidence thresholds, idempotent/retryable stages, and human-in-the-loop fallbacks, with monitoring focused on manual review and error rates to reduce false positives.”
Mid-level Cloud Data Engineer specializing in Azure/AWS pipelines and medallion architecture
“Data engineer focused on reliability and data quality, owning end-to-end pipelines processing ~100k–300k records/day. Implemented robust validation and monitoring that cut reporting issues by ~30%, and built stable external data collection with anti-bot measures, backfills, and schema-change detection while maintaining backward-compatible internal data services.”
Junior Full-Stack Software Engineer specializing in AI-powered applications
“Built and owns the full ProteinMenus AI pipeline end-to-end, spanning the iOS client, FastAPI backend, Gemini integration, Firestore, and Cloud Run deployment. Strongest signal is full-stack product ownership in an AI-driven consumer workflow, including monetization logic via an atomic credit system and architecture choices optimized for fast iteration after launch.”
Mid-level Data Analyst specializing in business analytics and BI
“Analytics professional with higher education experience at the University of Dayton, focused on turning inconsistent operational data into standardized metrics and recurring dashboards. They combine SQL, Python, and Power BI to automate reporting, improve data integrity, and reduce manual reporting by 30%, with outputs adopted in semester planning and cross-department performance tracking.”
Mid-level Software Engineer specializing in backend systems and real-time analytics
“Full-stack engineer at BigCommerce who combines customer-facing deployment ownership with hands-on AI/LLM systems work. Built and launched merchant analytics and predictive inventory workflows using React, TypeScript, FastAPI, Kafka, AWS, and RAG-style architectures, and has real production experience debugging non-deterministic AI issues caused by data pipeline freshness and event-ordering problems.”