Pre-screened and vetted.
Mid-level Software Engineer specializing in Data Engineering, ML, and Generative AI
Mid-level AI Engineer specializing in LLM agents, RAG, and production automation
Mid-level Full-Stack Software Engineer specializing in cloud-native apps and GenAI
Senior Cloud Security Engineer specializing in DevSecOps and multi-cloud security
Senior Full-Stack Developer specializing in AI-powered web applications
Senior Python Backend Engineer specializing in microservices, cloud, and healthcare/telecom platforms
Mid-level Full-Stack Developer specializing in FinTech web applications
Mid-level Full-Stack Software Engineer specializing in cloud backend and AI infrastructure
Mid-level Full-Stack Engineer specializing in FinTech and real-time distributed systems
Mid-level Backend Software Engineer specializing in Python microservices and cloud-native APIs
Mid-Level Software Engineer specializing in cloud-native microservices
Mid-Level Software Engineer specializing in cloud-native microservices on AWS
“Backend engineer with experience across healthcare and fintech platforms (Anthem, Citia) building high-throughput Python microservices with strong compliance/security focus (HIPAA, tenant isolation). Has integrated ML workflows into production systems (ResNet embedding-based image similarity) using async pipelines (Celery/Redis) and AWS (Lambda/S3/ECS), delivering measurable performance and fraud/content-integrity improvements at scale.”
Mid-level Full-Stack & AI Engineer specializing in cloud, data platforms, and LLM automation
“Software engineer/product builder who has owned an agentic affiliate lead-gen platform end-to-end (Django + React/TypeScript) and deployed it on Kubernetes in anticipation of 10x user growth from ~5K DAUs. Also has healthcare claims microservices experience using Kafka, including hands-on performance tuning to address consumer lag and broker pressure, and built an internal downtime alerting tool adopted across the organization.”
Senior Full-Stack Software Engineer specializing in API architecture and AI agentic RAG systems
“Hands-on backend/AI engineer who solo-built two production Claude-based agent systems: an internal Slack RAG over Confluence/Jira/code/regulatory docs and a HIPAA/GDPR-compliant patient chatbot with embedding guardrails and expert-in-the-loop evals. Also architected a multi-region patient portal + microservices platform with Terraform/CI-CD and federated gateways, delivering major onboarding automation and strong reliability wins (PgBouncer, chaos/perf testing).”
Junior Software Engineer specializing in full-stack systems and LLM automation
“Full-stack engineer who shipped a production "Financial Insight" assistant dashboard in Next.js App Router/TypeScript, integrating a RAG pipeline (embeddings + ChromaDB + LLM) via route handlers and owning post-launch performance (latency, token cost, retrieval relevance). Also built/optimized Postgres-backed workflows for an outbound dialer and callback routing engine handling ~10,000 daily contacts, validating query performance with EXPLAIN (ANALYZE, BUFFERS).”
“ML/NLP engineer with recent Scotiabank experience building production-grade indexing automation over large-scale emails and customer databases, combining LLM fine-tuning (Mistral, XLM-R) with fuzzy matching to exceed 95% accuracy under strict banking constraints. Also built a RAG-based chat agent using Gecko embeddings, Vertex AI Search, Gemini, and cross-encoder reranking, and delivered a text-to-SQL chatbot at SOTI through iterative fine-tuning and benchmark-driven experimentation.”
Senior Full-Stack Product Engineer specializing in Next.js, TypeScript, and distributed systems
“Full-stack engineer who built and shipped an analytics dashboard for search visibility using Next.js App Router/TypeScript with a server-components-first data strategy and server actions for interactivity. Designed and optimized the underlying Postgres analytics model and queries at scale, and implemented a durable Temporal-based indexing workflow with retries and idempotency—plus delivered a major frontend performance jump (Lighthouse low 70s to mid-90s).”
Senior Python Backend Engineer specializing in scalable APIs and cloud-native microservices
“Backend/data platform engineer who has built and operated a cloud-native media ingestion/processing platform in Python (Django/DRF, FastAPI) with Kafka, Postgres, and Redis, emphasizing multi-tenant security and reliability. Delivered AWS production systems combining EKS and Lambda with Terraform + GitHub Actions/Helm, and built Glue-based ETL pipelines with strong schema-evolution and data-quality practices; also modernized SAS analytics into Python on AWS. Seeking fully remote roles with a $120K–$140K base range.”
Senior Software Engineer specializing in cloud-native microservices (AWS, Java, Kafka)
“Backend engineer with hands-on experience modernizing high-volume transactional systems by decomposing monoliths into Spring Boot microservices on AWS, using Kafka for async workflows and Redis/SQL tuning for latency. Has built Python/FastAPI services with strong API contracts and production-grade security (OAuth2/JWT, RBAC, row-level security), and proactively hardened payment flows against race conditions and double-charging via idempotency.”
Intern Software Engineer specializing in AI/ML and computer vision
“Backend-focused Python engineer who owned and deployed EcoHero, a recycling guidance app using FastAPI + Firebase with barcode lookup, ZIP-code-based state rules, and user history tracking backed by 50 state datasets. Has hands-on Kubernetes + Docker experience and uses GitHub Actions and GitOps-style PR workflows for consistent deployments, plus event-driven async processing patterns with idempotency and retries.”
Mid-level Full-Stack Java Developer specializing in cloud-native microservices
“Software engineer with deep healthcare claims domain experience who has owned customer-facing portals end-to-end (Java/Spring Boot + React/TypeScript) and improved usability/performance based on real user feedback. Built microservices using REST and RabbitMQ with strong observability (Splunk/cloud metrics), and delivered an internal claims investigation dashboard that streamlined operations through centralized data, search, and filtering.”