Vetted Root Cause Analysis Professionals

Tashkeel Shah

Screened ReferencesStrong rec.

Senior Technical Artist specializing in real-time XR performance and rendering systems

10y exp

“UE5 gameplay/tech designer focused on VR and performance, with shipped systems spanning networked energy-driven Niagara VFX for a mobile VR live-concert MMO and an end-to-end performer avatar builder supporting editor/runtime and JSON-serialized UGC workflows. Known for deep profiling/debugging (Unreal Insights, Niagara CPU vs GPU emitter behavior) and for refactoring/optimizing animation and rendering across PC and mobile VR constraints.”

“Backend/ML engineer who has built both enterprise data pipelines and real-time AI products: modular Python (Flask/FastAPI) services integrating automation scripts and low-latency ML inference (MediaPipe, PyTorch) plus OpenAI-powered feedback. Demonstrated measurable performance wins (~30% faster HR workflows; ~40% faster AWS pipelines across 100+ Oscar Health feeds) and strong multi-tenant/data-isolation patterns (schema-based isolation, RBAC, microservices).”

“Cloud/SRE-style engineer at TDS supporting revenue-critical transportation SaaS platforms on AWS/GCP with Kubernetes. Has hands-on experience leading high-impact production work including DDoS mitigation, zero-downtime MSSQL→PostgreSQL migration using CDC, and building secure GitHub Actions + ArgoCD delivery pipelines and Terraform-based GKE infrastructure.”

“B2B lifecycle/CRM marketer running highly technical scientific service-line campaigns (multi-omics, translational sciences, ddPCR) using HubSpot segmentation, lead scoring, and multi-channel execution (paid social, ABM, and content syndication). Delivered measurable pipeline impact (200+ leads, 120 MQLs) and improved conversions 5–6% through cross-functional ICP refinement and multivariate testing.”

“ML engineer with hands-on experience taking a Gaussian Process Regression-based intelligent survey timing system from build to real-world deployment, including a 3-week RCT on 120 participants and measurable improvements (15% response rate, 23% data quality). Also served as a key technical resource at CData for customer-facing demos and debugging hundreds of production issues, bridging engineering with Sales and Customer Success.”

Naveen Chokkakula

Screened References

Senior Golang Engineer specializing in distributed systems and cloud-native microservices

Texas, USA5y exp

“Software engineer with experience at UWorld and Infosys, focused on full-stack product delivery and backend reliability. Stands out for owning analytics/onboarding experiences end-to-end while also building resilient distributed systems, reusable service primitives, and safe multi-tenant configuration guardrails.”

Mark Kevin Macadangdang

Screened ReferencesStrong rec.

Senior Solutions Architect specializing in enterprise integrations for PropTech and facilities management

Peterborough, Canada12y exp

“Facilities-management-focused functional consultant/business analyst with nearly a decade in CAFM/CMMS-aligned implementations since 2016, centered on MRI/FSI Evolution. Brings unusually strong depth across workflow automation, cross-system integrations, and finance/compliance-heavy operational processes, including SOR-based claims, contractor compliance, and RCTI invoicing.”

Nidhi Sharma

Screened ReferencesStrong rec.

Junior Software Engineer specializing in backend systems, AI, and cloud infrastructure

Noida, India2y exp

“Built multiple AI-heavy systems with a strong engineering lens on observability, reliability, and real-world usability, including an LLM gateway for auditability/failure isolation and Allyvision, an accessibility tool for visually impaired users. Also owned an end-to-end warehouse shipment tracking dashboard at Addverb Technologies that drove measurable operational gains, combining backend/data depth with frontend product execution.”

“Cloud/Linux infrastructure engineer focused on high-availability AWS platforms (EKS/EC2) with strong observability and incident response ownership. Has hands-on experience building secure CI/CD (GitHub Actions/Jenkins) and Terraform-based IaC at scale, including resolving real production issues like peak-traffic latency and Terraform remote state locking; transparent about not having direct IBM Power/AIX/PowerHA production ownership.”

“Analytics professional with hands-on experience spanning enterprise supply chain data and workforce analytics. They’ve worked on a Manhattan Active WMS implementation for a pharmaceutical client integrating MAWM, JD Edwards, and Boomi, and also built SQL/Python/Tableau solutions for BankUnited/FIU to standardize retention and engagement reporting. Strong fit for roles requiring messy data wrangling, KPI operationalization, and stakeholder-trusted dashboards.”

“Unity developer from the Naer project who built a natural-feeling VR wrist-flick gesture mechanic for teleport/push/pull interactions, validated through telemetry, low-FPS simulation, and diverse user testing with modular ScriptableObject tuning. Also handled Photon PUN 2 networking bug fixes (mid-air item state issues) and RPC optimizations while integrating AI tools (Claude/Gemini/ChatGPT) into planning and implementation.”

Anupreet Singh

Screened ReferencesModerate rec.

Intern Full-Stack Software Engineer specializing in AI and backend systems

Catonsville, MD1y exp

“AI intern who built core pieces of Cyberdome, a full-stack agentic compliance automation product using Next.js, Python, RAG, Qdrant, and NIST control retrieval. Stands out for combining frontend product work with backend LLM infrastructure, on-prem/local model deployment, and practical iteration based on user trust concerns around proprietary data.”

Rebecca Johnson

Screened ReferencesModerate rec.

Senior Product Manager specializing in AI workflows and healthcare SaaS

Remote, USA8y exp

“Homegrown product/program leader with 8 years of experience who has repeatedly found high-cost operational pain points and turned them into scalable product wins. Most notably, they built an address-validation and fraud-prevention system in non-emergency medical transportation that produced multi-million-dollar savings, and previously led an AI-assisted OCR workflow that raised accuracy to 98.6% and drove major efficiency gains.”