Vetted Agile Professionals

Paul Kasinski

Screened ReferencesStrong rec.

Executive CIO/CTO specializing in enterprise transformation across retail, e-commerce, and AI

Santa Monica, CA17y exp

“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).”

Peter Gluck

Screened ReferencesStrong rec.

Principal Software Engineer specializing in scalable, secure multi-platform systems

La Crescenta, CA14y exp

“Engineering leader and former CTO/Disney|ABC engineering manager who built white-label mobile app architecture that supported a branded app and successful exit, and later scaled Disney Channel brand app teams across iOS/Android/web and major OTT platforms. Led kid-safety architecture for DisneyNOW (“Junior mode” with PIN) and partnered with product/legal on COPPA compliance, emphasizing maintainable tech choices and strong execution processes.”

“Senior full-stack engineer with 5 years of experience across Bank of America, AT&T, and NextAI/XAI, building cloud-native, high-availability products spanning React, Node, Java, Kotlin, Python, and AWS. Particularly compelling for teams needing someone who can own architecture, implementation, DevOps, and UX polish end-to-end—from a real-time loan eligibility platform handling 50,000+ daily requests to live event dashboards that improved operations and helped drive $250K in ARR.”

Joshua Seiden

Screened ReferencesStrong rec.

Executive Technology & Product Leader specializing in emerging tech commercialization

Centennial, Colorado33y exp

“Startup operations/product advisor and long-time accelerator mentor who has helped multiple early-stage companies become enterprise-ready—shifting teams to customer-driven roadmaps and implementing CI/Agile delivery processes. Notably supported an Israeli company in landing a Fortune 30 customer before it later IPO’d on NASDAQ, and helped an Australian startup operationalize delivery to secure deployment with a major telecom and sports league.”

“Senior Engineering Manager with large-scale platform/API ownership at eBay, leading a globally distributed team and redesigning Order public APIs used by external developer ecosystems at ~800M requests/day, delivering 84% performance gains and reducing compute by ~300 VMs. Also led Google CRES ETL migration work on GCP, creating reusable Python libraries to standardize configuration across 10 integrations and improve developer productivity.”

“Explored a digital notarization startup concept in 2020 that stalled due to COVID-era inability to secure VC seed meetings; later saw the market validate the idea via a comparable acquisition (~$57M, per candidate). Now more interested in driving innovation and simplifying complex customer experiences within an established organization, using a highly structured, metrics-driven product execution approach.”

Shahla Almasri-Hafez

Screened

Director-level Engineering Leader specializing in mobile platforms and digital transformation

Remote, USA20y exp

“Mobile engineering leader who built Glassdoor's mobile org from 5 to 35 engineers while overseeing both iOS and Android. Started as a lead iOS engineer at CVS Health, moved into management, and combines hands-on technical depth with org building, talent development, and customer-driven product prioritization.”

“Built a production LLM-powered root cause analysis agent for supply chain alerts that helped operations managers avoid manual dashboard investigation. Demonstrates unusually strong depth in agent reliability, orchestration, and observability, with concrete production practices like hallucination blocking, shadow testing on 500 cases, and data-driven improvements that raised user agreement to 94% while cutting GPT-4 usage by 60%.”

“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, 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.”

“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.”

Dennis Noto

Screened

Executive Technology & Security Leader specializing in FinTech, AI platforms, and enterprise modernization

Denver Metro Area36y exp

“Technology transformation leader who builds board-approved roadmaps and scales engineering orgs with strong Agile execution. Led large modernization efforts (e.g., Scottrade: 3,000 programs/4M LOC in 18 months) and scaled POCs into enterprise SaaS platforms using Docker, Kubernetes, Helm, and Terraform for high-concurrency workloads.”

“Senior engineering executive-level leader with deep hands-on systems expertise across Amazon devices, Alexa, Echo, and FireTV/VegaOS. Unusually combines VP-level org leadership at 120+ scale with direct production debugging and architecture ownership, including hybrid edge-AI/cloud systems, partner platforms for 9000+ apps, and shipping long-horizon platform bets under aggressive release cadences.”

“PMO consultant with experience delivering regulatory and compliance-driven programs across financial services and government healthcare, including Citibank MRA remediation (Helios) and Ohio Department of Medicaid enterprise release management. Known for proactively consolidating fragmented project data into executive-ready reporting, driving cross-functional alignment, and operating with strong discretion in regulated environments.”

Kusumita Dasgupta

Screened

Director-level Engineering Leader specializing in data platforms, cloud systems, and LLM products

United States22y exp

“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.”

Sanket Patel

Screened

Director-level Front-End Engineering Leader specializing in scalable web and mobile apps

Palo Alto, CA17y exp

“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.”

“Full-desk recruiter with experience at Meta supporting the AR Glasses org, including a difficult Staff-level ML Engineer search. Uses competitor mapping (e.g., Snap/Microsoft/Google/Apple) and multi-channel passive sourcing (LinkedIn Recruiter, SeekOut, GitHub, Quora, network) while running a metrics-driven cadence with hiring managers and strong candidate advocacy.”

“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.”

“Engineering/data platform leader from FLYR (airline ML forecasting and automated pricing) who built scalable ingestion/ETL and a canonical data model to onboard airlines with highly heterogeneous source systems. Created a golden-metrics layer for airline KPIs and implemented monitoring/backfill capabilities, cutting onboarding time by 50%+ while improving SLA performance and controlling cloud/ML training costs through stronger data quality gates.”

“Operator focused on scaling and growing organizations, with experience in PE/VC-backed environments. Familiar with PE/VC and accelerator/studio models and how to apply them to create business agility and rapid experimentation while preserving innovation as companies scale.”

“Engineering leader with a mix of large-scale platform experience at Microsoft and product/customer-facing work across GM, Panasonic, Acuity, and other environments. Stands out for combining people leadership with hands-on depth in accessibility, web performance at 120M+ MAU scale, and cross-functional delivery spanning enterprise permissions, e-commerce, AI, and automotive systems.”

“Seasoned business leader with decades of leadership experience (including Fortune 50/500) and prior Silicon Valley startup exposure, now pursuing entrepreneurship. Building “Datascension,” a gamified, story/episode-based career coaching platform that includes hands-on tasks (e.g., SQL queries, Python scripts) plus a participation-based credit/currency system and certification/badging, informed by feedback from recruiters and coaching/recruiting firms.”