Pre-screened and vetted.
Mid-level AI Backend Engineer specializing in LLM applications and scalable ML services
Mid-level Software Engineer specializing in full-stack cloud and embedded systems
Mid-level Backend Software Engineer specializing in microservices and cloud APIs
Mid-level Software Engineer specializing in event-driven backend and on-device ML for robotics
Intern Data Scientist specializing in NLP and Large Language Models
VP Data Engineer specializing in AI-driven analytics platforms for investment management
Mid-level Data Engineer specializing in AI/ML data platforms and real-time streaming
Mid-level Data Engineer specializing in AWS, Spark, and streaming data pipelines
Mid-level AI Backend Engineer specializing in LLM applications and scalable ML systems
Intern AI/ML Engineer specializing in LLM applications and data infrastructure
“Hands-on LLM practitioner who built a production document-processing pipeline in Python, tackling long-document handling and latency with chunking/batching and a user-driven correction feedback loop. Experienced operationalizing AI workflows with Kubernetes (CronJobs, autoscaling, scheduled data cleaning and weekly retraining) and applying structured testing/evaluation (E2E, LLM-as-judge, HITL) while communicating solutions clearly to non-technical clients using visual diagrams.”
Mid-level Data Engineer specializing in cloud data platforms and FinTech analytics
“Solutions architect/technical consultant with experience across Intuit, Deloitte, and CodeNest Solutions, focused on enterprise data modernization, AI adoption, and real-time streaming in B2B environments. Particularly strong in regulated financial use cases, where they combine hands-on POC building, security/compliance diligence, and modern data stack expertise to help clients modernize legacy systems and close complex enterprise deals.”
Mid-level Software Engineer specializing in FinTech and scalable microservices
“Backend/platform engineer focused on high-traffic financial systems, owning real-time event-driven ingestion and Kafka streaming pipelines using Python/FastAPI, Avro schemas, and AWS services. Has hands-on Kubernetes (EKS) and GitOps/CI-CD experience (ArgoCD/Jenkins) and supported large-scale migrations from legacy VMs to containerized microservices with zero/low-downtime cutovers.”
Intern Software Engineer specializing in distributed systems and backend infrastructure
“Backend engineer with deep experience building event-driven logistics systems (orders, warehouse execution, real-time delivery tracking) using Spring Boot/PostgreSQL/Redis and strong observability (Prometheus/Grafana). Led a zero-downtime migration from monolithic MySQL to a sharded architecture for ~2M users with dual-write, checksum validation, and fast auto-rollback, and has strong security expertise including PostgreSQL RLS for multi-tenant SaaS and robust OAuth/JWT handling.”
Intern Software Engineer specializing in systems and full-stack web development
“Open-source contributor to a JavaScript visualization library who focused on runtime/rendering performance—eliminating unnecessary full redraws via memoization and diff-based updates validated with Chrome profiling. Also strengthened the project’s developer experience by adding TypeScript definitions, writing practical documentation, building minimal example apps, and handling community issues with reproducible debugging and public fixes.”
Senior Data Engineer specializing in multi-cloud data platforms and streaming pipelines
“Data platform engineer with hands-on ownership of high-volume financial data pipelines (millions of transactions/day) on Azure (ADF, Databricks, Delta Lake, Synapse), emphasizing schema-drift protection and automated data-quality gates. Also built resilient web scraping pipelines with anti-bot and backfill strategies, and shipped a versioned FastAPI + Redis data API with autoscaling, testing, and CI/CD via GitHub Actions.”
Senior Full-Stack Engineer specializing in Python, AI/ML, and cloud applications
“Backend/data engineer with hands-on production experience across FastAPI/PostgreSQL APIs and AWS (Lambda, ECS) delivered via Terraform + GitHub Actions. Built Glue-based ETL pipelines into Redshift with schema evolution and data quality checks, modernized legacy reporting into Python microservices, and has demonstrated measurable SQL performance wins (multi-second query reduced to sub-300ms).”