Vetted Incident Response Professionals

“Infrastructure/Unix engineer with production PowerHA/HACMP operations experience (resource groups, service IPs, shared storage) who has executed planned failovers and recovered a real outage involving a SAN driver crash and manual Oracle recovery (restored service in ~15 minutes with zero data loss). Also supports cloud DevOps practices including CI/CD security scanning (SonarQube, Snyk), container registry/versioning, and Terraform Cloud-based IaC across AWS and GCP with PR/Jenkins-driven plan-and-apply workflows.”

“Product-focused full-stack engineer with Walmart and Dell experience who built and shipped a real-time engagement dashboard end-to-end (Kafka Streams, Spring Boot, React/TypeScript/D3) used daily by business teams, moving them from next-day reports to real-time decisioning. Strong in performance/reliability (Redis caching cut latency ~40%, 90%+ test coverage, Prometheus/CloudWatch monitoring) and production operations on AWS/EKS including handling a cascading failure from a memory leak with zero-downtime rollback and redeploy.”

“Engineering manager with recent hands-on technical leadership in vendor-based geo augmentation, including making a key pivot from a broken vendor SDK to an internal data ingestion approach. Previously shipped impactful Python microservice refactors that reduced unnecessary data processing/storage and improved runtime payload efficiency, and has owned on-call incidents through mitigation (scaling pods) and prevention process changes.”

“Serial venture builder/operator across ad tech, media delivery, search engines, international content management, and ecommerce; has raised up to $150M and been involved in 8 acquisitions or IP-acquisition events. Known for refactoring/re-engineering smaller or troubled platforms into higher-value businesses, including building yield-management algorithms and a Kafka-like system to improve ad delivery profitability.”

“Backend/data engineer with strong AWS production experience across containers (ECS) and serverless (API Gateway/Lambda/SQS), plus Glue-based ETL to Parquet for Athena/Redshift. Demonstrates hands-on reliability and security depth (Cognito OAuth2/JWT with JWKS rotation, idempotency/DLQs, monitoring) and measurable performance wins (Redis caching + query tuning), along with legacy-to-services modernization using parallel-run parity and feature-flagged cutovers.”

“Customer-facing technical professional experienced in productionizing complex systems (including LLM/agentic workflows) and high-volume cloud data pipelines. Built and hardened a near-real-time data extraction/caching solution that significantly reduced latency and became a reusable pattern for other enterprise use cases; also runs developer demos/workshops with hands-on test environments and has driven 30–50% latency improvements.”

“Applied AI/ML Engineer at JPMorgan Chase who led a banker-facing LLM chatbot from an OpenAI-API POC to a production RAG workflow, including hallucination mitigation, automated evaluation in SageMaker, and operational monitoring with Dynatrace. Also delivers external technical education—hosted a hands-on Grace Hopper Celebration 2025 workshop teaching LangChain/LangGraph agentic workflows.”

“Senior engineer/tech lead with 18+ years building large-scale distributed applications, specializing in performance and reliability improvements. Recently owned multiple apps on an email personalization team, shipping major optimizations (including a push-update feature and audience-count architecture redesign) that reportedly lifted system performance from ~50% to ~99% while also leading code standards, reviews, and mentoring.”

“Platform-focused engineer experienced in productionizing ML/LLM systems: containerized a local prototype, implemented CI/CD, deployed to Kubernetes with scaling controls, and added monitoring/logging. Comfortable diagnosing real-time issues in LLM/agent workflows using logs/metrics and incident stabilization tactics, and supports sales calls by clearly explaining production scalability to unblock customer decisions.”

“LLM/RAG engineer who has shipped production systems in high-stakes domains (fraud analytics at Mastercard and security compliance as a CI/CD gate). Strong focus on reliability: hybrid retrieval for latency, citation-backed outputs for trust, and code-driven eval/regression pipelines using golden datasets. Also built scalable OCR-based ingestion for messy classroom artifacts (handwriting, PDFs, whiteboard photos) using Go/Python and cloud services.”

“Infrastructure reliability/capacity-focused engineer with hands-on IBM Power/AIX (LPAR/DLPAR, HMC, VIOS) performance troubleshooting and modern cloud-native delivery experience. Built production CI/CD and Terraform-managed AWS/EKS environments, and has led real incident recoveries spanning Kubernetes autoscaling and AWS quota constraints with concrete RCA and prevention improvements.”

“Robotics/control-focused engineer who built and validated a series elastic actuator control stack end-to-end (dynamic modeling, torque/position control, simulation, and experimental real-time debugging on hardware). Deep simulation background (OpenFOAM/COMSOL/Abaqus) and practical reproducibility tooling (Docker/CI), with conceptual ROS/ROS2 knowledge and confidence ramping into ROS-based stacks.”

“Capgemini engineer who helped take a travel insurance platform from prototype demos to a stable production system by clarifying requirements, hardening API contracts, and adding validation/logging to handle real customer data and external integrations. Experienced in real-time troubleshooting of complex workflows (including LLM/agentic-style workflows) through strong observability practices, and in leading practical developer-focused demos that accelerate client integration and adoption.”

“Backend engineer focused on multi-tenant enterprise AI personalization and recommendation platforms, combining ML/LLM intent extraction with deterministic policy guardrails for compliance and auditability. Has hands-on AWS experience (ECS/Lambda/DynamoDB/S3) and led a careful DynamoDB single-table migration using dual write/read, canary + feature-flag rollouts, and strong observability/security (JWT/OAuth2, RBAC, Postgres RLS).”

“Built and deployed an LLM + RAG + memory system on a Furhat social robot, adding continuous face/voice recognition embeddings over WebSockets to enable persistent, natural conversations across sessions. Experienced working around real-world hardware/latency constraints and uses Datadog plus structured debugging/rollback practices for stabilizing customer-facing LLM workflows.”

“AWS Solutions Architect intern who advised customers on securing a multi-tenant LLM-based SaaS, including isolation strategy tradeoffs and production guardrails against prompt injection. Has experience investigating a prompt-injection incident using logs/traces and TTP-style documentation, and designing scalable SDK/agent integrations via asynchronous worker architecture with prompt versioning.”

“Infrastructure-focused engineer with Vonage experience modernizing early-stage cloud architecture (Terraform modularization, blue-green deployments, containerization, and zero-downtime database migration planning to Aurora). Also built a local end-to-end side project, Vastu AI, combining a custom-trained YOLO model (Roboflow-labeled data) with a locally hosted LLM via Ollama to generate a vastu compliance report from floor-plan images.”

“Data engineer/platform builder with experience across PwC and Liberty Mutual delivering high-volume, production-grade pipelines and real-time data services. Has owned end-to-end streaming + batch architectures on AWS and Azure, including web scraping systems, with quantified reliability gains (99.9% availability, 90%+ error reduction, 30% latency reduction) and strong observability/CI-CD practices.”

“Platform-focused engineer/technical program leader working in silicon/wafer validation environments, with hands-on experience securing access to sensitive test results and engineering tooling. Has implemented RBAC/least-privilege controls with Azure Entra ID, Key Vault, PAM and integrated Checkmarx into dev workflows, while also deploying ML services on AKS using Bicep/Helm/Docker and Azure DevOps CI/CD with strong monitoring and incident response practices.”

“Software engineer at Cimpress owning end-to-end transactional pages for Pens.com (e-commerce). Built and integrated new discount experiences in a React/TypeScript + Node.js stack, focusing on modular component architecture to reduce tight coupling and avoid breaking existing functionality; prioritizes roadmap work using performance and conversion metrics.”

“Built a production internal RAG-based Q&A assistant at Huawei for ~4,000 engineers over a 12M-document Elasticsearch corpus, replacing link-only search with synthesized answers and achieving 87% user acceptance while keeping hallucinations under 0.4%. Pairs rigorous offline benchmarking (RAGAS, PR-gated F1 improvements) with human A/B testing and OpenTelemetry-based production monitoring, and also has strong Kubernetes/SRE experience orchestrating 50+ gRPC services with major MTTR and pager-fatigue reductions.”

“Senior engineering leader from Goodyear’s AndGo startup-like division who scaled the org from 12 to 30+ across pod-based teams and introduced an Architect Guild/ARD governance model. Led a 4-month Europe launch requiring AWS regional infrastructure, GDPR compliance, i18n/l10n, and new EMEA reporting pipelines, and has hands-on depth in API performance, incident response, and GraphQL/Hasura adoption to boost product velocity.”

“Full-stack engineer with strong DevOps/AWS production experience who builds and operates multi-agent AI systems end-to-end (Streamlit/Python through Docker/Kubernetes and ECS/Fargate). Has delivered measurable outcomes: sub-2s latency and ~92% routing accuracy for an AI wellness assistant, shipped an AI-for-BI prototype in under 6 weeks cutting analysis time ~40%, and improved pipeline iteration speed ~35% via modularization and CI/regression checks.”

“Engineering manager leading a 15-person team at FBN on the Gridbull platform, shipping a self-serve pricing/quoting tool for structured commodity products using real-time futures market data. Owns architecture and reliability for third-party data integrations (WebSocket + REST fallback), including resolving a day-one production incident caused by undocumented vendor connection resets. Introduced lightweight Technical Implementation Plans to improve cross-functional alignment and delivery speed in a high-growth environment.”