Pre-screened and vetted.
Principal Software Engineer specializing in cybersecurity distributed systems
Senior Software Engineer specializing in backend platforms and data systems
Senior Software Engineer specializing in full-stack platforms, MLOps, and LLM search
Senior DevSecOps Engineer specializing in secure cloud CI/CD and compliance automation
Mid-level Product Manager specializing in AI/ML data products for FinTech
Engineering Manager and ML/Data Architect specializing in scalable data platforms and personalization
“Hands-on engineering manager at a marketing company leading a highly senior, distributed team (10 direct reports) while personally coding ~60–70% and owning end-to-end architecture across three interconnected products. Built agentic CRM automation and a reinforcement-learning-driven distribution layer for channel spend/bidding, with a strong focus on scalable design and observability (Prometheus/APM/logging) enabling frequent releases and few production incidents.”
Executive Technology Leader specializing in digital, AI, cloud, and cybersecurity transformation
“CIO-level technology leader (most recently at Sovos) who owned the full tech roadmap across product, infrastructure, and corporate IT, scaling engineering across 14 countries with an architectural review board and standardized security/observability. Hands-on in high-severity incidents (ransomware) while managing executive/client communications, and drove a reported 40% product-velocity lift by adopting AI code assistants and agentic AI (Devin) alongside Kubernetes + Bottlerocket for secure scalability.”
Executive engineering leader specializing in cloud platforms, DevOps, and enterprise modernization
“Senior engineering leader with experience across cybersecurity, retail commerce, consulting, and media platforms, combining large-scale org leadership with hands-on architecture depth. Notable for driving measurable cloud modernization outcomes—multi-million-dollar cost savings, major latency and MTTR reductions, and compliance-heavy transformations—while also leading AI/NLP and consumer product simplification initiatives.”
Director-level engineering leader specializing in high-scale cloud platforms
“Engineering leader and player-coach with a long tenure leading 5 teams/17 engineers, combining organizational leadership with hands-on SQL, architecture, and production incident work. Particularly notable for shipping AI-powered lead engagement systems like an intelligent voice agent, while also driving operational improvements such as release cadence standardization, team restructures, database migrations, and major rules-engine performance gains.”
Executive engineering leader specializing in enterprise architecture, cloud, AI, and FinTech
“Engineering leader with experience modernizing e-commerce platforms and leading product strategy for data-driven franchise growth tools. Notable for scaling distributed teams, making pragmatic build-vs-buy and architecture decisions, and delivering measurable business impact including dramatically faster checkout performance and revenue gains.”
Senior DevOps Architect specializing in cloud and platform engineering
“Senior DevOps/infrastructure leader currently owning all DevOps for Audi Digital, including audiusa.com and its supporting cloud, CDN, CI/CD, and repository ecosystem. Stands out for delivering two simultaneous enterprise-scale migrations—100+ repo GitHub migration and Apollo Router supergraph platform migration—two months early with minimal disruption, while operating deeply hands-on in Kubernetes, containers, and cloud architecture.”
Executive Security Leader specializing in global risk, aviation security, and crisis management
“Operations and transformation leader who ran UPS Security through a major McKinsey-led restructuring, implementing a shared-services/territory-based "Patch of Land" model. Built task/time-based staffing models that enabled a 1K+ headcount reduction and $70M+ in recurring savings, earning the first UPS CEO Change Maker Award. Also mentors emerging leaders with simple, scalable operating rhythms (cadence meetings, decision frameworks, goal tracking).”
Executive technology leader specializing in cybersecurity, healthcare IT, and AI
“Seasoned global CTO and executive leader with 20+ years of experience, including a $389M non-founder exit to a Fortune 10 acquirer. Now building a pre-seed AI-driven diagnostic imaging platform for pets with web and mobile products, beta customers, and a patent-pending solution aimed at saving pet lives.”
Director of Engineering specializing in cybersecurity SaaS platforms and cloud-scale backend systems
“Director of Engineering at Proofpoint for 8 years, leading architecture and integration of Java microservices within a detection platform. Demonstrates pragmatic delivery leadership—incurring short-term cost to meet launch deadlines, then systematically paying down technical debt and optimizing AWS spend—plus a disciplined, long-horizon approach to backward-compatible API/schema evolution across many dependent services.”
Director of Engineering specializing in cloud-native SaaS, e-commerce search, and AI personalization
“Engineering leader (12+ years Director, 17 years lead) focused on developer productivity and platform/framework work across Oracle, PlayStation, Workday, and CafePress. Notable for building distributed teams from scratch and delivering high-impact platform architecture—e.g., re-architected PlayStation’s upload pipeline to support 500GB–5TB submissions using browser-to-AWS chunked uploads with SNS/SQS and deduplication/resume support.”
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).”
Senior AI Engineer specializing in LLM agents, RAG, and ML infrastructure
“Production-focused AI/ML engineer who has owned LLM agent and RAG systems end-to-end, from experimentation through deployment, monitoring, and iterative optimization. Stands out for building evaluation and observability layers around GenAI systems and delivering measurable gains in task success, regression detection speed, and token efficiency in production.”
Engineering Manager specializing in MLOps/DevOps and CI/CD for deep learning platforms
“Player-coach engineering leader focused on AWS ML infrastructure and deep learning image delivery: provisioned EKS/Kubernetes for multi-node training and automated image release pipelines (Python + AWS CDK) to cut release time from 2 weeks to 1. Also built customer migration tooling for SageMaker HyperPod and owned a security incident end-to-end, implementing prevention tests and process improvements.”
Mid-level Software Engineer specializing in autonomous vehicle operations and test automation
“Hands-on Python/IoT engineer with experience spanning research labs and autonomous vehicles (Zoox), focused on making data/decision-support systems reliable in production. Has deployed and Dockerized Python tools with pinned dependencies, built sensor-based on-prem data collection systems (aquafeed evaluation), and troubleshot telemetry issues down to a failing switch port using logs, multimeter checks, and network diagnostics.”
Mid-level Software Engineer specializing in backend systems and cloud data platforms
“Candidate is a hands-on engineer using AI as a controlled coding partner rather than an autonomous decision-maker. They have practical experience designing and leading structured multi-agent coding pipelines with specialized roles for code generation, review, and test coverage, and show strong judgment around reliability through schemas, guardrails, reviewer gates, and manual validation.”
Senior Site Reliability Engineer specializing in production LLM/RAG deployments
“Built and operationalized an internal LLM/RAG system for engineering specs—starting with an at-home prototype using real ERP documents, then securing hardware, standing up a GPU/software stack, and deploying through UAT to production. Identified organizational gaps (no shared spec repository) and created a queryable RAG database that reportedly cut document discovery from days/weeks to minutes, while also resolving retrieval issues via improved PDF-aware chunking.”