Pre-screened and vetted.
Mid-level DevOps Engineer specializing in cloud-native infrastructure on AWS and Azure
“DevOps/SRE focused on cloud-based distributed systems, with strong hands-on Kubernetes production experience (microservices deployments, Helm, probes, resource tuning, CI/CD and Docker build standardization). Demonstrated end-to-end troubleshooting across application, infrastructure, and networking layers—e.g., isolating degraded storage via node disk I/O metrics and restoring performance by draining the node and replacing the volume. Builds Python automation for operational reliability, including scheduled Kubernetes secrets rotation integrated with an external secret manager.”
Director-level QA Engineering Manager specializing in cloud platform quality & reliability
“AWS engineering manager leading delivery for an end-to-end encrypted communications product (calling/messaging/screen sharing), including shipping read receipts with full design/engineering/QA ownership. Demonstrated strong customer-driven problem solving (offline/mission users enrollment via admin one-time codes with account allowlisting) and reliability improvements (data retention bot crash RCA, monitoring/notification, and high-volume test simulation).”
Mid-level Software Development Engineer specializing in robotics and cloud-based device management
“Amazon Robotics engineer who deployed and scaled the Lumos camera-based package scanning work cell across EU sort centers (100+ work cells in 5+ sites), enabling remote launches via detailed runbooks and troubleshooting. Strong in AWS IoT/edge systems, with hands-on incident recovery (restored 34 down work cells) and secure multi-compute certificate provisioning using IoT Jobs, ACM/CA, and custom roles; delivered ~75% per-cell cost reduction vs Cognex-based approach.”
Senior Software Engineer specializing in AI orchestration and backend systems
Senior DevOps/Platform Engineer specializing in Kubernetes and Go backend automation
Executive Engineering Leader (VP/CTO) specializing in cloud-native platforms and AI/ML
Senior Software Engineer specializing in agentic AI and scalable backend systems
Senior DevSecOps Engineer specializing in secure cloud-native CI/CD platforms
Senior Full-Stack Software Engineer specializing in cloud and enterprise web platforms
Senior Full-Stack Engineer specializing in scalable cloud platforms and AI integrations
Executive Enterprise Technology Transformation Leader specializing in cloud, platforms, and operations
Executive CISO specializing in global cybersecurity, technology risk, governance & compliance
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).”
Mid-level Cloud/DevOps Engineer specializing in AWS platform automation and CI/CD
“Senior infrastructure/platform engineer with deep IBM Power/AIX (Power9, VIOS, HMC, LPAR/DLPAR) and PowerHA production ownership at scale (40 frames / ~300 LPARs), including hands-on outage recovery and performance tuning. Also delivers modern DevOps/IaC capabilities—CI/CD for Kubernetes microservices and Terraform-based multi-account AWS (EKS/VPC/IAM/RDS) with drift detection and safe rollout controls.”
Senior Backend Engineer specializing in distributed systems and cloud microservices
“Backend/data engineer with experience at Nike building high-volume order orchestration and validation APIs using FastAPI microservices on AWS EKS with Kafka, Redis, and Postgres. Strong in production reliability (timeouts/retries/idempotency), GitOps (Argo CD) + Terraform deployments, and data pipelines (AWS Glue/S3), with hands-on incident ownership and legacy modernization into API-driven services.”
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.”
Senior Infrastructure Engineer specializing in cloud, Kubernetes, and MLOps
“LLMOps-focused technical leader who took an LLM use case from prototype to production for a non-technical customer by combining trust-building and structured enablement with a robust AWS/Kubernetes-based MLOps stack. Built observability and rollback mechanisms (Grafana + MLflow) to troubleshoot in real time, and scaled delivery by hiring a 5-person team while partnering with sales to manage expectations and drive adoption across departments.”
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).”
Engineering Director specializing in backend & data platforms for enterprise SaaS and cybersecurity
“Backend/data engineering player-coach on a UEBA cloud security analytics platform who standardized MLOps and detection development for 180+ detections, cutting ship time from 6–7 weeks to ~3 weeks while reducing false positives. Proven at operating large-scale streaming + Spark systems (200K+ events/sec, 100+ TB/day), driving major reliability/cost improvements, and leading incident response and team execution through GA.”
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.”
Director-level Front-End Engineering Leader specializing in scalable web and mobile apps
“Amazon engineer/leader who drove a major modernization of the AWS Database Migration Service Console, migrating a monolithic UI to a micro-frontend architecture while improving performance, reliability, and engineering standards. Operates as a player-coach (80/20 hands-on/management), with demonstrated incident ownership and process improvements across Amazon and Walmart Labs.”
Mid Software Engineer specializing in distributed backend systems
“Engineering candidate deeply embedded in AI-native development, currently using tools like Cursor and Claude Code to generate most of their code and building internal agents for on-call monitoring, anomaly detection, and automated incident mitigation. Particularly interesting for teams exploring AI-first engineering workflows, multi-agent development setups, and operational automation at scale.”
Executive CISO/CTO specializing in global cybersecurity, risk management, and compliance
“Founder building a digital transformation startup that combines execution, GCC/center-of-excellence setup to fund transformation via labor arbitrage savings, and an AI/data analytics platform with live dashboards. Previously delivered multiple Fortune 500 transformations and created fraud-detection value by reusing in-vehicle cybersecurity data to identify warranty and odometer rollback fraud; currently raising capital through executive/board networks and Silicon Valley investors.”