Vetted Adaptability Professionals

“Backend/platform engineer with hands-on ownership of Python services (Postgres/Redis/Celery) and measurable performance gains (~20–25%). Strong Kubernetes + ArgoCD GitOps experience delivering zero-downtime rollouts, plus led key reliability fixes (readiness probes, immutable tagging) and supported an on-prem to AWS migration using CDC replication and ALB traffic shifting; also built Kafka real-time analytics pipelines with schema registry.”

“Operations/people-ops leader focused on early-stage, growth, and turnaround environments, with hands-on experience implementing UKG (HRIS) and Lever (ATS) to scale without adding headcount. At Niagen Bioscience, drove a 25% improvement in time-to-fill and cut administrative workload by 30% in 6 months, led a company-wide optimization initiative to reduce silos, and coached a VP of Finance into a successful CFO transition that included restructuring the finance org and upgrading key talent.”

“Growth creative lead at Amazon who ran structured, incrementality-informed A/B tests for Prime acquisition on Amazon DSP. Produced a winning benefit-led video + social-proof framework that improved CTR/CVR while cutting CPA (-24%) and increasing ROAS (+32%), then scaled the approach across email and onsite placements for an additional 10–12% lift in Prime sign-ups.”

“Post-sales SAP CRM implementation professional with experience at IBM and Malam Team, owning full lifecycle delivery from requirements and process design through configuration, testing, and end-user training. Notably built an SAP UI5 service center dashboard that cut SLA-miss tickets from 20% to 5% and regularly drove cross-functional alignment to unblock complex technical issues.”

“LLM/AI engineer with production experience building a retrieval-based document intelligence system that extracts information from PDFs/emails, backed by Python + Spark pipelines. Focused on reliability and cost/latency optimization (caching, batch processing) and has hands-on orchestration experience with Airflow (sensors, retries, alerts). Also partnered with business stakeholders to deliver customer feedback classification/summarization for faster sentiment insights.”

“AI engineer with production experience building a high-accuracy (98%) fraud detection system operating at real-time latency (1–2s) over millions of transactions, using a multi-model pipeline approach to meet performance constraints. Also implemented Airflow-orchestrated workflows (DAGs, retries, alerts) to replace brittle cron scripts and is currently pursuing a master’s project on real-time ASL-to-text conversion.”