Pre-screened and vetted.
Principal Software Architect specializing in AI/ML and cloud-native full-stack platforms
“AI/LLM engineer who built a production content-generation system for nursing education, combining multimodal RAG over proprietary PDFs (including images) with structured Cosmos DB data and external sources. Strong focus on production reliability—prompt-chaining with LangChain, validation/guardrails, and Azure-based monitoring/observability—plus experience designing Azure AI agents with tool integrations like Bing Search.”
Principal Unity/C# Developer specializing in mobile and live-service games
“Unity gameplay developer who led implementation of an airport scene for Duplo Town (children’s physics/exploration game), adding multiple unspecced interactions that significantly increased polish and playfulness and delighted testers/clients. Principal/lead-level engineer with strong sprint planning and impact-vs-effort prioritization, plus experience designing asynchronous client-server interactions and state management (aware of Photon-style real-time multiplayer sync).”
Mid-level Machine Learning Engineer specializing in GenAI, LLMs, and real-time ML systems
“Built and deployed a production long-form article summarization system using BART/T5/PEGASUS, tackling real-world constraints like token limits, latency/quality tradeoffs, and factual drift via chunking/merge logic and constrained decoding. Uses pragmatic Python-based pipeline orchestration (scheduled jobs, modular scripts, logging/retries) and iterates with stakeholder feedback to make outputs genuinely useful for content workflows.”
Mid-level AI/ML Engineer specializing in NLP, fraud detection, and MLOps
“LLM/ML platform engineer with hands-on experience taking an LLM document summarization prototype into a production-grade service on AWS EKS, emphasizing low-latency inference, drift monitoring, and safe CI/CD rollouts (canary + rollback). Strong in real-time debugging of agentic/RAG systems (tracing, retrieval/index drift fixes) and in developer enablement through practical workshops (Docker/Kubernetes/FastAPI) plus pre-sales support via demos and benchmarks to close pilots.”
Mid-level Full-Stack Java Developer specializing in cloud microservices
“Full-stack engineer who built a policy management and notifications platform end-to-end: Java/Spring Boot microservices with PostgreSQL plus a React/Redux UI, deployed on AWS with Docker and Jenkins CI/CD. Demonstrates strong real-world scaling and reliability practices (Redis caching, Kafka, query/index tuning, ACID transactions, locking, and idempotent processing) to handle high-volume concurrent workloads.”
Mid-level Full-Stack Software Engineer specializing in cloud and AI-enabled applications
“Product-focused full-stack engineer (70/30 app vs infra) with Accenture experience and recent AI workflow work, shipping end-to-end systems from React/TypeScript UIs through FastAPI backends to Postgres. Built an AI-driven data extraction platform with async job APIs, strict schema validation, and strong observability, and has operated AWS ECS-based deployments with real incident mitigation (DB connection exhaustion/latency under traffic spikes).”
Mid-level Full-Stack Developer specializing in FinTech and Healthcare systems
“Open-source contributor who improved React Query’s caching/subscription behavior to reduce unnecessary re-renders via debouncing and batched updates, validated with benchmarking and extensive tests. Also maintained a Flask extension and resolved production background-task hangs by tracing Redis connection handling issues, adding cleanup/retry logic and troubleshooting docs. In a fast-paced startup, owned the design of a Celery+Redis multi-queue background processing system with Prometheus-based observability.”
Mid-level Full-Stack Java Developer specializing in cloud-native microservices and FinTech
“Full-stack Java engineer (4+ years) who led end-to-end modernization of high-latency order management systems into cloud-native reactive microservices (Spring WebFlux) and built real-time React/Redux dashboards, reporting 99.98% uptime and 22% infra cost savings. Also headed a production RAG-based Order Support Bot at Dell Technologies with embeddings + MongoDB semantic search, automated validation and human fallback, plus CI/CD-driven LLM eval loops to reduce hallucinations.”
Mid-level Full-Stack Engineer specializing in cloud-native microservices (FinTech/Healthcare)
“Built and shipped production systems spanning real-time operational dashboards and an LLM-powered internal documentation assistant using RAG (embeddings + vector DB). Demonstrates strong focus on reliability and iteration: implemented guardrails and evaluation loops (human review, hallucination tracking, regression prevention) and improved performance/scalability through query optimization, caching, and retrieval tuning.”
Senior Full-Stack Java Engineer specializing in cloud-native microservices and FinTech
“Backend engineer who owned a Python task management API with JWT auth, async notifications, and performance work (DB optimization/caching) to handle high volumes. Led an on-prem to Azure private cloud migration at Morgan Stanley using GitOps and IaC (Terraform/ARM) with phased rollout and rollback planning. Also built a Kafka real-time streaming pipeline with exactly-once/idempotent consumers and Prometheus/Grafana monitoring.”
Senior Technical Lead specializing in accessible, scalable web applications
“Frontend lead who shipped an enterprise social feed, insights dashboard, and a net-new communications platform using React + TypeScript. Known for building scalable quality practices with QA (including automated test suite alignment), introducing RTK Query org-wide, and managing phased, feature-flagged rollouts while coordinating closely with product/design and senior engineering stakeholders.”
Mid-level Full-Stack Java Engineer specializing in microservices, cloud, and event-driven systems
“Software engineer at Procter & Gamble focused on warehouse/operations systems, building near-real-time order/inventory visibility using Java/Spring Boot, React, Kafka, PostgreSQL, and Redis with measurable latency and load-time gains. Also shipped internal LLM/RAG knowledge assistants grounded in company runbooks and workflows, implementing guardrails and an evaluation loop that drove concrete retrieval improvements (document chunking) and regression prevention.”
Junior Full-Stack Software Engineer specializing in Django, AWS, and AI/ML
“Full-stack engineer who built and owned an AI-powered personal statement editor in Next.js (App Router + TypeScript), including dynamic routing, server-side data fetching, and typed API route handlers. Post-launch, they handled production monitoring/debugging and shipped reliability/performance upgrades (rate limiting, retries, rollback, DB indexing), and report a 40% latency reduction using Suspense/streaming and React concurrency patterns. Also implemented a durable Temporal-orchestrated AI document workflow with robust retry/idempotency strategies.”
Junior Full-Stack/Systems Engineer specializing in AI, embedded systems, and healthcare apps
“Led architecture for “Solstice/Solstis,” a safety-aware, hands-free AI medical assistant that guides users through minor emergencies with a structured, state-machine-driven LLM agent integrated with device hardware. Built RAG grounded in Red Cross procedures plus guardrails, fallbacks, and emergency escalation, and improved real-world usability by shifting from open-ended chat to a deterministic step-by-step workflow measured via completion rate, repeat prompts, and latency.”
Mid-level Full-Stack Software Engineer specializing in Java/Spring microservices and AWS
“Backend/platform engineer who has owned a real-time business analytics dashboard backend (Python/Flask/MongoDB) and built Kafka event-streaming pipelines with idempotent processing and DLQs. Strong DevOps/GitOps experience deploying containerized microservices to AWS EKS with CI/CD (Jenkins/GitHub Actions/CodePipeline) and ArgoCD auto-sync/drift detection, plus hands-on support for phased hybrid cloud/on-prem migrations using feature flags and replication.”
Mid-level Full-Stack Engineer specializing in cloud-native microservices and DevOps
“Backend engineer with strong Python/FastAPI microservices ownership, including an ML-serving service with embeddings, async DB access, and Redis caching to reduce latency under high load. Experienced deploying and operating containerized services on Kubernetes using GitOps (Argo CD/Helm) with automated CI/CD, plus hands-on Kafka streaming pipeline tuning and enterprise migration work (Infosys) using blue-green/active-passive strategies.”
Mid-level Software Engineer specializing in FinTech backend systems
“Built and deployed an AI-driven expense categorization workflow integrating OpenAI API and PGVector to automate general ledger coding. Stands out for combining LLM/embedding architecture with finance operations context, stakeholder-facing deployment ownership, and measurable impact of roughly 30%+ reduction in manual coding effort.”
Junior Software Engineer specializing in full-stack and iOS development
“Built and shipped a production Python service integrating with a helium mass spectrometer for real-time sensing and remote control/monitoring. Combines hardware integration, observability, and Playwright-based automation expertise, with a strong track record of turning brittle or ambiguous real-world processes into reliable systems— including reducing dashboard automation failures from about 20% to under 2%.”
Mid-level Software Engineer specializing in Java microservices for FinTech
“Engineer working on high-throughput financial systems who uses AI pragmatically to accelerate development without sacrificing design ownership, correctness, or compliance. Particularly interesting for teams building regulated, real-time platforms: they have hands-on experience integrating fraud detection models into microservices, handling transaction ingestion, scoring, decisioning, and throughput-sensitive asynchronous workflows.”
Mid-level AI Engineer specializing in LLMs, RAG, and production ML systems
“Built and shipped an AI-powered RAG diagnostic assistant at Ford for EV technicians, integrating GPT-based models with LangChain, FAISS, and SageMaker into real technician workflows. Stands out for combining strong production LLM architecture with practical safety guardrails, monitoring, and measurable impact: 45% better diagnostic accuracy and roughly 30 minutes saved per case.”
Mid Software Engineer specializing in FinTech and ML-powered backend systems
“Backend-leaning full-stack engineer who has shipped real-time, customer-facing dashboards and ticketing/payment features at Freshworks and Global Payments. Strong in Python API design (Django/Flask/FastAPI) and React/TypeScript UIs, with hands-on experience scaling PostgreSQL for high transaction volumes and operating services on AWS, including incident response and HIPAA-aligned security controls.”
Mid-level Full-Stack Software Engineer specializing in AI and cloud-native platforms
“Dell engineer with hands-on full-stack and AI-powered internal platform experience, spanning React/TypeScript frontends, Spring Boot/Python microservices, Kafka streaming, and AWS/Kubernetes deployment. They’ve owned monitoring and anomaly-detection products end to end, including a dashboard that reduced manual log review and helped teams detect issues roughly 30% faster, while also translating complex AI outputs into intuitive experiences for non-technical users.”
Junior Full-Stack Developer specializing in FinTech and Healthcare platforms
“Frontend-focused engineer with experience spanning AI interview coaching and institutional financial dashboards. Stands out for combining user-centered UI design with deep browser-performance work, including reducing dashboard lag via virtualization and building low-stress, progressive-disclosure interfaces for anxious job seekers.”
Junior Software Engineer specializing in full-stack and AdTech systems
“Front-end engineer with nearly 2 years of React experience who independently owned a revamp of an internal ad tech platform as the sole front-end engineer. Stands out for handling complex conditional UI flows, collaborating across product/design/backend, and proactively improving usability and performance through techniques like debouncing, virtualization, and TypeScript.”