Pre-screened and vetted.
Executive engineering leader specializing in AI-native platforms and distributed systems
“Engineering leader and hands-on architect from Sony Pictures Entertainment who has led large-scale platform modernization, digital supply chain delivery, and multiple GenAI/RAG initiatives in media and rights-management domains. Notable for combining people leadership with deep AWS/LLM architecture work, including a 1M+ record GenAI title search system and AI-driven contract insights that reportedly helped unlock a 20% revenue increase.”
Senior Backend Engineer specializing in GenAI, LLMs, and scalable data pipelines
“Backend/ML platform engineer from Snapsheet who owned production Python services and data pipelines for insurance claims, including an AI document classification/summarization FastAPI service on ECS/Fargate processing 1M+ documents/year. Strong in AWS infrastructure (Terraform, CI/CD, secrets/IAM, autoscaling), Glue/PySpark ETL with schema evolution controls, and legacy SAS-to-microservices modernization with safe, feature-flagged rollouts and measurable performance wins.”
Senior Full-Stack Engineer specializing in Java microservices and cloud-native platforms
“Backend-focused engineer with Walmart Global Tech experience building shipment and seller workflow systems using Spring Boot, GraphQL, Kafka, and async processing. Stands out for improving bulk label API performance by 60-75%, designing item-level partial-failure workflows that improved user clarity, and also exploring AI-powered debugging/RCA platforms with Java, Python, LangChain, and LLM integrations.”
Junior Applied AI Software Engineer specializing in LLM agents and RAG systems
“Engineer focused on AI-powered developer automation and agent-driven software delivery, with experience spanning customer-facing edtech and internal tooling. They describe building a K-12 chatbot-based learning platform for the York Region public school system and creating internal automations like code-generation pipelines and diff summarization tools adopted across teams, alongside work on legacy encrypted messaging systems at Instagram/Meta.”
Executive engineering leader specializing in AI, data platforms, and cloud SaaS
“Senior engineering executive with a rare mix of VP-level people leadership and deep hands-on architecture across cloud-native and AI platforms. He led secure hybrid SaaS design at Promethium, built GenAI-powered analytics with LLMs/RAG, and translated customer needs into product wins including the largest deal in company history and a PLG motion that generated 100+ leads.”
Director-level Engineering Leader specializing in data platforms, cloud systems, and LLM products
“Engineering leader/player-coach with recent hands-on work delivering an agentic AI MVP on Amazon Bedrock (conversational UI + supervisor agent routing between internal knowledge and external sources). Previously drove large-scale data platform cost optimization at Twitter, saving ~$3M–$5M annually, and has owned production incidents end-to-end with a focus on analytics/monitoring improvements and team coaching.”
Mid-level Machine Learning Engineer specializing in LLMs, RAG, and search systems
“Backend/ML infrastructure engineer with experience at Perplexity and Meta building production evaluation, monitoring, and retrieval systems for AI search, autonomous agents, and LLM-powered workflows. Particularly strong in turning messy manual quality-review processes into reusable Python/FastAPI automation with measurable impact, including major gains in search relevance, latency, and grounded answer quality.”
Mid-level AI/ML Engineer specializing in Generative AI, RAG, and MLOps
“AI/LLM engineer with production experience at NVIDIA and Microsoft, including building a RAG-based enterprise knowledge assistant that improved accuracy by 42% and scaled to thousands of queries. Deep in inference optimization (TensorRT-LLM, Triton, quantization, speculative decoding) and MLOps/observability (Prometheus/Grafana, MLflow, LangSmith), plus orchestration with Kubeflow/Airflow across multi-cloud.”
Junior Machine Learning & Data Science professional specializing in LLMs and analytics
“Amazon internship experience building production GenAI analytics for the returns organization: a multi-agent LLM+RAG system that let analysts query multiple heterogeneous data sources in natural language without hand-written SQL. Also built and operationalized four Apache Airflow DAGs for large-scale ETL, emphasizing observability and freshness-aware metadata to keep outputs accurate and up to date.”
Senior Technical Account Manager specializing in cloud, AI, and enterprise platforms
“AWS Technical Account Manager with 5 years supporting large enterprise customers on cloud migrations, application development, and architecture decisions across a broad AWS stack. Stands out for combining enterprise cloud advisory with hands-on solution building—from POCs and DR designs to a custom mobile and automation workflow for a construction client that won CEO buy-in and changed field operations.”
Mid-level Software Engineer specializing in full-stack systems and distributed platforms
Mid-level Software Engineer specializing in backend systems and data platforms
Senior Software Engineer specializing in AI/ML, search, and recommendation systems
Director of Machine Learning specializing in GenAI platforms and enterprise AI/ML
Senior Full-Stack Software Engineer specializing in cloud-native microservices and AI platforms
Mid-level Machine Learning Engineer specializing in LLMs, RAG, and scalable GPU inference
Intern Machine Learning Engineer specializing in LLMs, RAG, and model quantization
Senior Full-Stack AI/ML Engineer specializing in cloud data platforms and GenAI
Principal Machine Learning Scientist specializing in GenAI, LLMs, and RAG
Mid-level AI/ML Engineer specializing in LLMs, RAG, and production MLOps
Senior Applied AI Engineer specializing in LLMs, NLP, and production AI systems