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Vetted Load Balancing Professionals
Pre-screened and vetted.
Junior Software Development Engineer specializing in AWS cloud services and SDN
Mid-level Machine Learning Engineer specializing in LLMs and RAG systems
Mid-level Full-Stack Software Developer specializing in Java microservices and React on AWS
Mid-level Site Reliability Engineer specializing in AI training infrastructure and GPU platforms
Executive IT and cybersecurity leader specializing in enterprise infrastructure and security operations
Senior Data Engineer specializing in cloud data platforms and real-time analytics
Ajeeta Asthana
Mid-level Software Engineer specializing in distributed systems and FinTech infrastructure
“Early-career software engineer who owns revenue-critical invoice processing and internal ops tooling end-to-end. Has built TypeScript/React systems backed by MongoDB and Temporal, and designed scalable SQS-based onboarding workflows with FIFO/DLQ monitoring. Notably redesigned an Authzed SpiceDB authorization model, shrinking a 500+ line schema to ~20 lines while meeting sub-100ms p95 latency.”
Shiting Ding
Mid-level Software Engineer specializing in Ads backend and ML infrastructure
“Customer-facing technical professional with Amazon incident-management experience who helps drive adoption of complex ML/LLM solutions by delivering hands-on demos and rapid model fine-tuning. Applies a disciplined debugging approach (repro + logs/metrics + severity triage) and maintains runbooks to resolve SEV2 issues in ~1 hour, while also partnering with sales/customer teams to ship patches and new features based on feedback.”
Benjamin Ung
Senior Machine Learning Software Engineer specializing in computer vision and simulation
“Robotics engineer who worked on a lunar rover program, building a simulation environment that mirrored real hardware interfaces and incorporated moon-terrain slip/friction modeling validated against a physical “moon yard.” Also integrated an ML-based munition X-ray inspection system via REST APIs, deploying and scaling inference on Azure with Kubernetes plus Prometheus monitoring, load balancing, and self-healing reliability mechanisms.”
Dhruv Arora
Senior Generative AI Implementation Consultant specializing in RAG and agentic AI on cloud
“LLM/RAG practitioner who built an AWS-based enterprise document search and summarization platform with RBAC and scaled it to 10K+ users, solving relevance issues via contextual chunking and hybrid retrieval. Also designed agentic workflows for a telecom forecast-validation use case using sub-agents, tool APIs, and strict context management, and has proven pre-sales influence (supported a $300K manufacturing deal with a roadmap-driven pitch).”
Mid-level Software Engineer specializing in robotics, AI, and full-stack systems
Senior Cloud DevOps Engineer specializing in AWS/Azure platform engineering
Senior Full-Stack Engineer specializing in cloud-native microservices and AI/LLM integrations
Junior Software Engineer specializing in backend systems and distributed infrastructure
Junior Software Engineer specializing in AWS cloud infrastructure and ML systems
Senior Full-Stack Software Engineer specializing in AWS cloud-native microservices and healthcare platforms
Mid-level Full-Stack Developer specializing in Java microservices, React, and cloud AI platforms
Senior AI/ML Engineer specializing in Generative AI and LLM applications
Intern Computer Vision/ML Engineer specializing in mapping, localization, and scalable inference
Senior AI and Full-Stack Engineer specializing in Healthcare IT and FinTech
Director-level Software Architect specializing in cloud observability and network monitoring