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Vetted Amazon Bedrock Professionals
Pre-screened and vetted.
Mid-Level Backend Engineer specializing in SaaS automation and data platforms
Junior Software Engineer specializing in AI/ML systems and LLM-powered document automation
Junior Software Engineer specializing in cloud observability and distributed systems
Junior Software Engineer specializing in scalable systems and cloud infrastructure
Mid-level Software Engineer specializing in payments, data platforms, and ML systems
Senior Solution Architect and Engineering Manager specializing in government, FinTech, and cloud platforms
Staff-level AI/ML Engineer specializing in LLM agents and RAG for e-commerce
Executive Technology Leader (CIO/CTO) specializing in cloud platforms, cybersecurity, and digital transformation
Senior Software Engineer specializing in GenAI, RAG, and multi-tenant SaaS platforms
Mid-Level Software Development Engineer specializing in AWS serverless, security, and ML platforms
Mid-level Machine Learning Engineer specializing in fraud prevention and LLM systems
Technology Executive specializing in AI-native engineering and cybersecurity governance
Mid-level AI/ML Engineer specializing in LLM evaluation, RAG, and GPU-accelerated inference
Staff Software Engineer specializing in enterprise SaaS, AI assistants, and distributed systems
Mid-level Software Development Engineer specializing in AWS incident management and AI analytics
Mid-level AI/ML Data Engineer specializing in data pipelines, MLOps, and LLM/RAG systems
Peeyush Dyavarashetty
Intern AI/ML Engineer specializing in GenAI, LLMs, and agentic RAG systems
“AI/LLM practitioner who built a GPT-2-like language model from scratch at the University of Maryland using PyTorch and multi-GPU distributed training, with experiment tracking in Weights & Biases. As an AI Operations intern at ScaleUp360, delivered multiple production-style AI agent automations (Gmail classification and Fireflies-to-Claude workflows that extract and assign CEO tasks) and set up measurable evaluation using test cases and classification metrics.”
Pavan Devulapalle
Mid-level Software Engineer specializing in cloud platforms and AI-integrated full-stack development
“Backend engineer who built Flask-based internal APIs supporting GenAI-driven provisioning/diagnostics (Outpost/AWS Outposts-like environment), with deep hands-on optimization across Postgres/SQLAlchemy (2s to <200ms endpoint improvement). Experienced integrating ML/LLM workflows via AWS SageMaker and Bedrock, and designing multi-tenant isolation plus high-throughput Redis-backed background task pipelines (minutes to seconds).”
winston lo
Junior Software Engineer specializing in AI agents, RAG, and full-stack development
“Backend engineer who built and iterated a secure, multi-tenant RAG system over a large document corpus, emphasizing strict RBAC/ACL isolation, hybrid retrieval (vector+keyword), reranking, and strong observability to balance relevance, latency, and cost. Also led production refactors/migrations using strangler + feature flags/dual writes and has experience catching subtle real-world failure modes (including in a sensor calibration optimization pipeline).”
Vishnu Mukundan Thanikunathe Manoj
Junior AI/ML Engineer specializing in LLM agents, explainable AI, and computer vision
“Robotics/computer-vision engineer with industrial safety monitoring experience, building real-time pose estimation (TRTPose) and 2D-to-3D localization and optimizing pipelines to sustain 30+ FPS under heavy multi-entity load. Also brings edge-to-cloud distributed systems work (HoloLens + Google Vision/Translation) and production ML deployment experience using Docker/CI/CD across finance and edge camera environments.”