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Vetted Data Validation Professionals
Pre-screened and vetted.
Junior Data Analyst / ML Engineer specializing in analytics pipelines and recommendation systems
Junior Software Engineer specializing in ServiceNow, data engineering, and AWS
Senior QA Engineer specializing in test automation, API testing, and performance testing
Senior QA Engineer specializing in POS and payment processing systems
Mid-level AI/ML Engineer specializing in Generative AI, LLMs, and RAG for financial services
Senior SDET specializing in UI/API automation and cloud-native quality engineering
Mid-level Applied AI Engineer specializing in reliable LLM agent workflows for regulated domains
Mid-level Data Engineer specializing in cloud-native ETL and data warehousing
Mid-level AI/ML Engineer specializing in NLP, MLOps, and financial risk & fraud analytics
Mid-level Data Engineer specializing in AWS lakehouse and Spark pipelines
Junior Data Analyst specializing in finance, supply chain, and GTM analytics
Mid-level QA Engineer specializing in manual and automation testing for web, mobile, and APIs
Mid-Level Full-Stack & Cloud Engineer specializing in scalable distributed systems
Mid-level Backend/Data Engineer specializing in legal data pipelines and APIs
Kshitij Singh
Intern Software Developer specializing in healthcare data and systems analysis
“Candidate comes from SaaS and healthcare analytics rather than game development, but has strong end-to-end ownership experience building real-time, high-availability systems in Python/AWS. They highlight measurable impact across performance, throughput, uptime, and cost reduction, including queue optimization and predictive ICU utilization pipelines, and are looking to transfer that systems engineering foundation into Unity/gameplay work.”
NEHA KOLAN
Mid-Level Software Engineer specializing in microservices and cloud data pipelines
“Full-stack engineer with end-to-end ownership across React/TypeScript frontends, Spring Boot/Node microservices, and production ops on Docker/Kubernetes and AWS (ECS/CloudWatch). Built real-time healthcare eligibility and analytics systems at Cigna and an early-stage seller onboarding platform at Flipkart, driving measurable performance gains (35–40% latency/throughput improvements) through event-driven Kafka pipelines, Redis caching, and strong reliability/observability practices.”
Caden Cheah
Intern Full-Stack/ML Engineer specializing in LLM applications and mobile development
“Backend engineer who built a serverless AWS Lambda microservices backend for a parenting assistance mobile app, including a personalized recommendation system optimized to sub-500ms via precomputed scoring and DynamoDB caching. Demonstrates strong production pragmatism: CloudWatch-driven performance tuning (provisioned concurrency), zero-downtime phased schema migrations, and robustness patterns like optimistic locking and request deduplication. Also led a refactor of an LLM RAG pipeline to improve retrieval quality and cut latency from ~5s to ~3s.”