Vetted Cost Optimization Professionals

“NYC-based startup founder/CTO who sold products to Omnicom and Sprinklr, then built an AI-powered cultural insights engine inside Omnicom using AWS Lambda + ML to process ~1M items/day and reached ~$1MM ARR in year one. Former senior leader at Sprinklr managing 200+ people globally, delivering enterprise martech solutions with SLAs and high-reliability social data pipelines (Twitter firehose).”

“Operations/engineering leader from Poly who optimized a professional headset portfolio by aggressively prioritizing technical debt and consolidating HW/SW platforms (down to 2 each), accelerating time-to-market by ~6 months and enabling 3–6 month variant cycles. Also drove AI-enabled quality improvements by leveraging JIRA bug data to automate test case creation and expand coverage, while aligning engineering and product management around MVO delivery.”

“CTO-focused candidate with experience at foundations evaluating startups, including reviewing technical architectures and coaching teams to refine ideas for better platform fit and synergies. Prioritizes company culture and integrity when choosing leadership roles.”

“Commercial/GTN leader with GCP experience managing multi-year, multi-megawatt AI/GPU infrastructure commitments, owning segment P&L and governance for take-or-pay/reserved capacity. Drove a major client partnership scaling ARR from $50M to $100M in 18 months by aligning Product/Engineering, GTM, and infra teams and building flexible, margin-protective commercial structures. Known for speeding hyperscaler procurement/security reviews (FedRAMP/SOC2, IAM, data residency) and operationalizing multi-region delivery with landing zones and IaC.”

“Engineering/technology leader with IBM Cloud experience leading large-scale infrastructure modernization from classic architecture to a standardized VPC/next-generation DC platform. Reports major outcomes including cutting region launch time from ~18 months to ~3 months and reducing operating costs by ~80% via automation, modular undercloud services, and platform standardization, while scaling a globally distributed org with clear service ownership and accountability.”

“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.”