Pre-screened and vetted.
Mid-Level Full-Stack Software Engineer specializing in cloud-native web applications
“Full-stack engineer who has owned customer-facing and internal web portals end-to-end (API, database, React UI, and deployment). Experienced designing multi-service architectures with Node/Express and Java/Spring Boot plus RabbitMQ/Kafka messaging, emphasizing contract/versioning discipline, observability, and operational tooling that measurably reduces support load and manual work.”
Mid-level Backend Software Engineer specializing in cloud-native microservices and FinTech
“Backend-focused engineer with Mastercard experience building and operating high-volume transaction-processing microservices. Has owned customer-facing banking services end-to-end and built an internal on-call analytics tool that centralized logs/metrics with real-time filtering to speed root-cause analysis and reduce incident investigation time.”
Junior Machine Learning Engineer specializing in geospatial analytics and computer vision
“Built and evolved a geospatial ETL + API platform that processes pixel-wise satellite imagery in PostgreSQL/PostGIS into low-latency farm-level time-series metrics for an interactive dashboard, using precomputed hotspot analysis to reduce latency by 75–80%. Experienced in FastAPI-style API contract design (OpenAPI), caching, server-side filtering/compression, and production-minded security patterns (RBAC, session-derived authorization, password hashing) with disciplined rollback/versioning practices.”
Mid-level Full-Stack Developer specializing in React and scalable web applications
“Backend/data engineer with hands-on production experience across FastAPI microservices and AWS data platforms. Has delivered serverless and Glue/EMR-based ETL pipelines with strong observability (Prometheus/Grafana/Sentry, CloudWatch/SNS), schema-evolution resilience, and measurable SQL performance wins (5 min to <30 sec). Open to onsite meetings in the Bethesda, MD area and flexible on remote arrangements.”
Mid-level AI/ML Engineer specializing in NLP, LLMs, and RAG systems
“Backend engineer who built and evolved a PHI-compliant RAG system (FastAPI + LangChain + embeddings/FAISS) for internal document search and summarization, delivering <400ms p95 latency at ~2,500 daily requests and measurable impact (30% faster investigations, +17% retrieval relevance). Demonstrates strong security and rollout discipline (RBAC/RLS/JWT, redaction/audits, shadow mode, dual writes, canaries) and a focus on reducing hallucination risk via grounded guardrails and confidence-based fallbacks.”
Intern Software Engineer specializing in robotics, embedded systems, and AI
“Senior design robotics engineer on a "Grocery Robot" project selected for the final round of the $10K SICK Challenge, owning ROS2 system design and behavior-tree-based task orchestration across multiple independently developed modules. Also implemented I2C/ESP32 collision avoidance, IK control for a robotic arm, and a Node.js ordering system, with additional research experience using RPLIDAR-based SLAM.”
Junior Mechatronics Engineer specializing in robotics, embedded systems, and mechanical R&D
“Lead hardware/integration engineer on a high-speed autonomous drone for adversarial drone tracking and surveillance, owning the full stack from custom electronics and flight-controller tuning to ROS2 SLAM and GPU-accelerated computer vision. Built a custom USB-based ROS2 LiDAR driver and migrated SLAM from SLAM Toolbox to Google Cartographer, while boosting YOLOv5 tracking from ~2 FPS to ~45 FPS on an NVIDIA Jetson through CUDA/dependency optimization.”
Junior Full-Stack Java Developer specializing in Spring Boot microservices and React
“Full-stack Java/Spring Boot + React engineer (3–4 years) who built an end-to-end smart employee management system and a data analytics dashboard handling millions of daily transactional records. Emphasizes scalable layered REST API design, secure microservices practices (Spring Security, JWT/OAuth2), and performant React state/data patterns (Redux Toolkit + RTK Query) for large datasets and role-based views.”
Mid-level AI/ML Engineer specializing in Generative AI, NLP, and healthcare RAG systems
“Built and deployed a production clinical claim validation RAG system at GE HealthCare that automated nurses’ patient-history/claims checks, cutting manual review time by ~65%. Designed the full stack (retrieval, embeddings, Pinecone, prompt/verification guardrails, FastAPI backend) with PHI-compliant anonymization via NER and orchestrated pipelines using Airflow, Azure ML Pipelines, and MLflow with drift monitoring.”
Mid-level AI Engineer specializing in healthcare claims analytics and RAG copilots
“Built a production "appeals co-pilot" for a healthcare claims appeals team, combining an XGBoost/logistic ranking model with a Python/LangChain RAG stack (FAISS + Mistral 7B) to surface high-probability appeal wins and speed policy-grounded drafting. Emphasizes reliability and trust: hybrid retrieval with metadata routing, citation/eval scripts, guardrails, and an explainability layer that non-technical stakeholders could understand and override.”
Senior Full-Stack Software Engineer specializing in AI-first cloud-native systems
“End-to-end engineer who has productionized AI automation and RAG capabilities, building full-stack systems (React/Node/Redis/Postgres + vector DB) with evaluation-driven quality gates and monitoring. Reported ~60% reduction in manual ops time and major turnaround improvements, and has experience modernizing legacy systems safely via feature flags and parallel runs while working across product, data, and ops teams (System1).”
Mid-level Software Engineer specializing in Java microservices and AWS
“TypeScript backend/full-stack engineer who owned an internal business workflow platform end-to-end in production, including API/data design, relational DB integration, and enterprise integrations. Has hands-on experience operating workflow processing services with Kafka-style event-driven patterns, idempotency, exponential backoff retries, dead-letter queues, and strong observability, plus API design with OpenAPI/Swagger and token-based auth.”
Mid-Level Software Engineer specializing in data engineering and cloud platforms
“Backend-leaning full-stack engineer who has shipped production-critical data/reporting features at Walmart and built an end-to-end workflow automation product (FastAPI + React/TypeScript + PostgreSQL) deployed on AWS. Strong in performance/reliability engineering (parallel ETL, batch DB operations, indexing via EXPLAIN ANALYZE), secure API design (JWT/RBAC), and pragmatic incident-driven scaling (separating workers from API layer).”
Mid-level Full-Stack Java Developer specializing in cloud-native FinTech and Healthcare platforms
“Backend engineer with production experience building and scaling a Java/Spring Boot payment processing API on AWS (PostgreSQL/Redis) handling a few thousand RPS, including deep performance debugging (connection exhaustion) and observability (CloudWatch, Actuator, Zipkin). Also shipped application-layer AI features (OpenAI email summarizer with feedback loop, ~40% faster agent response times) and designed reliable multi-step workflow orchestration with retries and manual escalation, plus strong SQL tuning and Python engineering practices.”
Senior Software Engineer specializing in distributed systems and cloud-native platforms
“Backend-leaning full-stack engineer with experience at Walmart, Qualtrics, and American Express, shipping secure partner-facing API platforms and internal monitoring dashboards. Strong in AWS production operations (ECS/Fargate, RDS/Postgres, CloudWatch) plus rigorous testing/security practices, with measurable delivery and performance improvements (35% faster releases; ~30–40% latency reductions).”
Executive Technology Leader specializing in SaaS platforms, AWS microservices, and security
“Platform/infra engineer with deep Kubernetes (EKS) and VMware vSphere experience who has led a monolith-to-microservices transition for a credit lending decision platform. Built GitOps-driven Terraform delivery with strong governance, and used LaunchDarkly-based progressive rollouts plus Datadog observability to safely ship multiple times per day (reported ~6x throughput and 1/3 the bugfix tickets vs legacy). Also operates hybrid on-prem/AWS networking (firewall + Transit Gateway, BGP) and has handled high-stakes datacenter migrations (100TB Storage vMotion) under Sev1 conditions.”
Mid-Level Software Engineer specializing in cloud-native microservices and FinTech platforms
“Software developer with hands-on experience refactoring a legacy .NET CMS into a newer API-driven application (ASP.NET MVC, JavaScript/HTML), including dynamic asset migration and resolving team merge conflicts in Bitbucket. Built automated tests with PyTest and used Postman for API validation, and leveraged Splunk for production issue detection; also worked on an end-to-end ticketing/workflow management project with prioritization and verification steps.”
Mid-level Data Engineer specializing in cloud lakehouse platforms and ETL/ELT
“Accenture data engineer who greenfielded a supply-chain lakehouse platform, building an end-to-end medallion/Delta pipeline ingesting ~1.4TB/day from 17+ ERP/WMS/TMS/shipment sources. Delivered Gold datasets to Redshift/Synapse/Databricks SQL powering Power BI/Tableau with a 99.5% SLA, while cutting runtime 30% and cloud costs 16% through Spark/Delta optimizations and robust data quality controls.”
Mid-Level Full-Stack Software Engineer specializing in cloud-native web platforms and observability
“Built and shipped production LLM agents including an AI patient appointment assistant for Kyron Medical that automated specialist matching and end-to-end booking with email/SMS confirmations and a voice mode. Strong focus on production reliability (double-booking prevention with DB constraints and pre-write checks), deterministic multi-step orchestration with LangGraph, and rigorous monitoring/evaluation using LangSmith trace replay for prompt regression testing.”
Senior Data Engineer specializing in cloud data platforms and real-time analytics
“Data engineer (Credit One) who built and owned real-time financial transaction and credit risk/fraud data systems end-to-end on AWS + Snowflake. Delivered high-scale pipelines (150k events/hour; ~2TB/week), raised data accuracy to 99%, and cut Snowflake costs 42% while adding strong observability, schema-drift handling, and production-grade APIs/documentation.”
Mid-level Machine Learning Engineer specializing in Healthcare AI and Generative AI
“Analytics professional with Intuit experience spanning modern data stack work, behavioral segmentation, and applied AI. They built dbt/Snowflake pipelines powering retention and churn dashboards, automated feedback classification with OpenAI/LangChain, and partnered closely with product and marketing teams to turn analytics into onboarding, targeting, and lifecycle messaging decisions.”
Mid-level Software Engineer specializing in AI/ML and full-stack systems
“Data Scientist (2–3 years) at ZS Associates who has built and productionized agentic LLM systems, including a LangGraph-based multi-LLM prompt-optimization pipeline for entity extraction deployed as a Spring Boot microservice via Jenkins. Also built an Insightmate.ai chatbot and improved its RAG accuracy by diagnosing vector retrieval issues and implementing HyDE query expansion, while partnering with sales and pharma stakeholders to drive adoption (e.g., Zimmer Biomet platform migration into a multi-year partnership).”
Mid-level Data Analyst specializing in BI, analytics automation, and cloud data platforms
“Analytics professional with hands-on experience building SQL/Python pipelines, customer ID mapping logic, and self-serve BI dashboards across marketing/CRM and regulated aviation reporting environments. Particularly strong in turning messy multi-source data into trusted reporting assets, with repeated claims of major efficiency gains, faster decision-making, and high-confidence stakeholder adoption.”
Junior Software Engineer specializing in full-stack development and AI platforms
“Built and owned VividCraft end-to-end, a production AI platform spanning a TypeScript/Next.js frontend and a Python backend with FastAPI, Celery, Redis, PostgreSQL, and AWS. Stands out for reliability-focused systems thinking: designed idempotent job orchestration across 9 AI providers, shipped with extensive automated test coverage, and reports zero production regressions after launch plus zero credit loss through provider outages.”