.png){kind=logo}
Vetted Software Development Engineers
Pre-screened and vetted.
Michael Kaufman
Mid-Level Full-Stack Software Engineer specializing in mobile and web platforms
“iOS-focused engineer who led feature development for Amazon Books/Kindle (e.g., Series & Story So Far recaps, Kindle Memories) and introduced pure Swift packages while building sync and content download systems. Also has full-stack experience (React/TypeScript + Node with REST/GraphQL) and strong AWS operations (CDK/CI-CD, CloudWatch, canaries, autoscaling), plus founder experience at GLXY.ai shipping an early hardware MVP (weight sensors) under tight constraints.”
Mid-level Software Development Engineer specializing in cloud platforms, data engineering, and LLM apps
Junior Software Development Engineer specializing in AWS cloud services and SDN
Mid-level Full-Stack Engineer specializing in scalable cloud web services
Mid-Level Software Engineer specializing in AWS cloud-native distributed systems
Mid-Level Software Development Engineer specializing in cloud microservices and retail systems
Entry-Level Software Development Engineer specializing in AWS serverless and distributed systems
Mid-level Software Engineer specializing in cloud infrastructure and backend systems
Mid-level Site Reliability Engineer specializing in AI training infrastructure and GPU platforms
Staff Software Engineer specializing in agentic AI and conversational systems
Entry-Level Software Engineer specializing in full-stack web and gaming platforms
Mid-level Full-Stack/Backend Software Engineer specializing in distributed systems and cloud
Mid-level Full-Stack Software Engineer specializing in distributed systems and GenAI platforms
Junior Software Engineer specializing in AI infrastructure and applied machine learning
Junior Software Development Engineer specializing in IoT, robotics, and machine learning
Mid-level Software Engineer specializing in AI infrastructure and machine learning
Junior Software Development Engineer specializing in AWS automation and data pipelines
Venu Dave
Junior Software Development Engineer specializing in backend data platforms and LLM applications
“Amazon internship experience building and shipping an end-to-end NL-to-SQL system: ingested/normalized metadata across 60+ internal tables, added rigorous multi-layer validation for LLM-generated SQL, and served it via a FastAPI backend for engineers—driving 90%+ faster dataset discovery and ~70% lower effort to access data. Also built an early-stage RAG-based healthcare assistant, iterating on chunking, embeddings, and retrieval to improve answer quality post-launch.”
Yashvi Shah
Mid-Level Software Engineer specializing in distributed systems and cloud platforms
“Amazon Alexa engineer who architected and shipped a GenAI Knowledge Agent used by 2M+ customers, focused on making LLM outputs auditable via citations and a verification layer that prevents hallucinations. Built the full vertical slice (FastAPI/LangChain backend + React/TypeScript streaming UI) while keeping p99 latency under 200ms, and has proven incident response experience on AWS (Lambda/DynamoDB scaling issues).”
Ashi Sinha
Junior Software Engineer specializing in full-stack and ML/NLP systems
“Entry-level full-stack engineer with internship experience at Amazon (Appstore IAP flow + uninstall recommendation workflow) and a health-tech startup (OneVector) where they built a DSUR reporting workflow end-to-end, including document generation, S3-backed versioning/metadata, and secure preview/download. Demonstrates strong production debugging and reliability mindset (instrumentation, deterministic retrieval, idempotent writes) and focuses on UX/performance in high-stakes user flows.”
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.”