Pre-screened and vetted.
Mid-level Data Engineer specializing in AI/ML and cloud data platforms
Junior financial engineering analyst specializing in portfolio analytics and data science
Senior Software Engineer specializing in cloud platforms for healthcare and e-commerce
Mid-level Machine Learning Engineer specializing in real-time recommender systems and MLOps
Mid-level AI/ML Engineer specializing in LLMs, RAG, and multi-agent systems
Senior Data Scientist specializing in large-scale ML systems and recommendations
Mid-level AI/ML Engineer specializing in NLP, computer vision, and recommender systems
Senior Machine Learning Scientist specializing in LLMs, RAG, and health AI
Executive CIO/CTO specializing in enterprise transformation across retail, e-commerce, and AI
“Senior technology executive (CTO/SVP Technology, also board member) with experience modernizing legacy environments and scaling teams in high-growth and PE-owned contexts. Architected a standardized enterprise platform (ERP/WMS/CRM/POS/eComm/DWH/BI/integration) to rapidly migrate acquisitions—moving 7 companies in under 3 years and cutting migration timelines ~4x—while also driving major org redesign and hiring acceleration (30+ hires in 6 months).”
Executive CIO/CTO/CISO specializing in cloud, AI/ML, and cybersecurity transformation
“Fractional CTO and AI/ML consultant at Clover Health with deep insurance domain experience (15 years as CTO/CISO/AI). Has spent significant time in PE/VC-backed environments (including Aquiline Capital Partners and Apollo Group), designing and engineering platforms while delivering against budgets, audits, and regulatory compliance. Recently helped build an insurance startup (2020–2025) and is now seeking a full-time role at a startup.”
Senior Data Engineer specializing in real-time data platforms and lakehouse architectures
“Senior, product-focused engineer who has built real-time customer-facing web applications and a microservices backend (TypeScript/React/Node) using RabbitMQ, MongoDB, and Redis. Demonstrates strong operational maturity (idempotency, tracing/observability, backpressure) and built an internal console that became the primary tool for debugging, replaying jobs, and managing system behavior.”
Executive Engineering Leader specializing in AI-driven SaaS and IoT platforms
“Engineering leader who built and delivered an IoT smart-spaces platform for the self-storage and smart-living domains, translating customer requirements into architecture, capability maps, and a multi-milestone roadmap. Personally stood up missing AI/ML capabilities (including churn prediction) using Databricks (Delta Lake/MLflow), enabling follow-on features like energy optimization and security/anomaly detection. Scaled an org from 20 to 80+ with disciplined Agile planning (Jira Advanced Roadmaps/Confluence) and strong executive/customer-facing leadership during high-stakes customer commitments.”
Director of Security & Data Platform Engineering specializing in AI-driven cloud security
“Player-coach engineering leader focused on scalable data security scanning and risk detection in hybrid cloud, owning architecture and core implementation of an incremental/parallel DSPM scanning engine. Shipped production improvements including 60% lower scan latency and 30% fewer false positives, with strong emphasis on correctness under concurrency, multi-tenant observability (SLOs/burn-rate alerts), and disciplined rollout practices (feature flags, shadow scans, canaries).”
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 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.”
VP Software Engineering Manager specializing in full-stack platforms, data, and AI in FinTech
Executive AI & Data Technology Leader specializing in buy-side and capital markets platforms
Mid-level Data Analyst / BI Analyst specializing in analytics, governance, and dashboards
Senior Full-Stack Software Engineer specializing in cloud-native microservices and AI platforms