Vetted Incident Response Professionals

“Hands-on engineering manager/lead focused on Azure application deployments and CI/CD automation. Has led design sessions and 1:1 code reviews, and owned a production performance incident end-to-end from measurement and test-environment setup through production validation, while coaching team members via regular 1:1s.”

“Built and shipped production systems spanning real-time operational dashboards and an LLM-powered internal documentation assistant using RAG (embeddings + vector DB). Demonstrates strong focus on reliability and iteration: implemented guardrails and evaluation loops (human review, hallucination tracking, regression prevention) and improved performance/scalability through query optimization, caching, and retrieval tuning.”

Jax Diagana

Screened

Senior AI Engineer specializing in forward-deployed voice agents and incident-response automation

San Francisco, CA7y exp

“FDE at Bland.ai and founder of Fi (incident-response agent) who routinely takes LLM/agentic concepts from prototype to production. Has hands-on experience reverse-engineering undocumented systems to deliver integrations, building LLM testbeds for voice-agent reliability, and rapidly shipping RAG/semantic search solutions (e.g., Confluence runbooks) after deep customer discovery with DevOps/SRE teams.”

Mukundan Sridharan

Screened

Executive Technology Leader (CTO) specializing in IoT sensing, AI/ML, and RF/embedded systems

Rockville, MD22y exp

“Currently a startup CTO who thrives on building new technology stacks and rapidly turning technical ideas into products. Interested in partnering with a CEO/business team to commercialize embedded/edge concepts such as multi-sensor drone localization (video/audio/RF with SDR), low-cost solar+battery power nodes networked via LoRa, and an Amazon Sidewalk/LoRa connectivity device with cloud management.”

Vu Tran

Screened

Senior Product Manager specializing in 0–1 platforms, AI workflows, and product operations

Oakland, CA8y exp

“Customer success/product-facing operator from AllRoomie (AI-powered rental marketplace) who owned an enterprise real estate brokerage account end-to-end. Improved conversion and adoption by automating lead intake/routing and fixing integration issues, citing ~40% less manual coordination, faster response times, and expansion into additional regions through ROI-driven land-and-expand motions.”

Utkarsh Chandel

Screened

Senior Security Engineer specializing in detection engineering, cloud security, and DFIR

San Francisco, CA8y exp

“LLM workflow/agentic systems practitioner who has helped customers harden an LLM-based incident triage prototype into a trusted daily-use production system by adding observability, audits, confidence gating, and deterministic fallbacks. Brings an SRE-style approach to real-time debugging (trace replay, rollback/canary, safe toggles) and is experienced running developer-centric demos/workshops and partnering with sales on technical qualification and security/architecture artifacts.”

“Has worked across multiple startup stages from pre-funding through Series D and emphasizes rigorous idea validation through direct conversations with both end users and purchasing decision-makers. Interested in applying NLP to automate summarization/abstracting of highly technical articles, with a balanced view of entrepreneurship that prioritizes health and family.”

“Full-stack product engineer with hands-on ownership of both a real-time community Q&A platform and a production payroll reorder batching system. Stands out for combining backend architecture, React frontend work, and pragmatic performance improvements, including a 2-3x speed gain through batching and thoughtful UI/UX refinements that reduced user errors.”

“Backend engineer with hands-on ownership of banking microservices from initial design to launch and production support, including security, CI/CD, observability, and incident response. Stands out for measurable modernization impact—~35% faster backend processing, ~40% lower query latency, and ~30% better deployment cycles—and for a pragmatic approach to both Kafka-based async systems and controlled LLM integration in enterprise workflows.”

“Growth-focused B2B SaaS operator with hands-on experience improving enterprise adoption for a cloud governance and FinOps platform. They combine customer discovery, ROI-driven messaging, automation, and funnel instrumentation to improve conversion and handoffs, citing an 18% lift in enterprise adoption and roughly $200K-$3M in influenced pipeline.”

“Customer-facing technical professional with experience supporting LLM/agentic-style workflows and complex integrated systems (APIs, backend logic, databases). Partnered with sales/customer teams at Radix Health to onboard new clients in phased prototypes, translating non-technical requirements into technical scope and implementing core product changes to tailor the appointment-booking solution for providers.”

“Software engineer with experience at Walmart and Amex building customer-facing backend services and microservices at scale (RabbitMQ). Built an internal developer tooling platform integrating Figma with GitHub Copilot to automate consistent React component creation, adopted across multiple teams; emphasizes fast, safe iteration using metrics, feature flags, gradual rollouts, and automated testing.”

“Cloud/Kubernetes-focused production engineer with experience running 99.95% uptime platforms across AWS/Azure/GCP. Strong in incident response and performance troubleshooting (including a 30% MTTR reduction), and in building secure CI/CD and Terraform-based IaC for AKS/GKE microservices with robust change controls and rollback practices. Notably does not have direct IBM Power/AIX/VIOS/HMC or PowerHA/HACMP ownership.”

Sai Nekkanti

Screened

Mid-level Data Scientist / ML Engineer specializing in secure GenAI and financial compliance

Mount Laurel, NJ4y exp

“Built a production "sentinel insight engine" to tame information overload from millions of product reviews and support transcripts, combining Azure OpenAI (GPT-3.5) zero-shot classification with a fine-tuned T5 summarizer to generate weekly actionable product insights. Demonstrated strong MLOps/production engineering by adding drift monitoring with embedding-based detection, integrating REST with legacy SOAP/queue-based CRM via FastAPI middleware, and scaling reliably on Kubernetes with HPA.”

Navindu Jayatilake

Screened

DevOps Technical Lead specializing in Kubernetes, AWS, and platform engineering

Colombo, Sri Lanka6y exp

“Sri Lanka–based DevOps/Platform engineer focused on Kubernetes and AWS who has led real production incidents and recoveries (network-policy-induced asymmetric routing; node pool failure due to CNI upgrade). Built production CI/CD with GitHub Actions (ephemeral self-hosted runners on EKS), ArgoCD, Vault, and Terraform, and led a phased ECS-to-EKS migration including Kafka consumers and MongoDB Atlas private endpoints.”

“Frontend-leaning full-stack engineer who built and fully owned a production crew scheduling system at Archer using Next.js App Router/TypeScript, including a real-time, virtualized timeline handling ~1,200 crew over a 30-day window. Drove major post-launch improvements (60 FPS scrolling, PubNub-based soft-locking to cut conflicts ~90%) and created a correlation-ID-driven state replay/logging tool to debug hard-to-reproduce production issues while also contributing to FastAPI/SQLAlchemy/Postgres performance work.”

“Candidate appears to work at the intersection of enterprise billing/payments systems and AI-powered support automation. They describe owning customer deployments, integrating PayPal/Stripe, building LLM/RAG workflows for finance operations, and handling production incidents affecting millions of invoice events with measurable improvements in resolution time and ticket volume.”

Saicharitha Yanamandala

Screened

Mid-Level Software Developer specializing in Java, Cloud, and Microservices

Chicago, IL6y exp

“Backend/Python engineer who owned an end-to-end FastAPI + AWS internal natural-language document Q&A system (Textract extraction, embeddings/vector DB, LLM integration) with strong focus on reliability and latency. Hands-on with Kubernetes + GitOps (Argo CD, Helm, rolling updates/auto-rollback) and built/optimized Kafka streaming pipelines using Prometheus/Grafana. Also supported a zero-downtime on-prem to cloud migration with parallel run and gradual traffic cutover.”

Luis Aragon

Screened

Senior Software Engineer specializing in data infrastructure and distributed systems

San Francisco, CA6y exp

“Software engineer working on agentic AI SMS customer engagement flows and a Customer Data Profile service that unifies journey data across SMS/web/calls while enforcing precise consent management. Has hands-on production operations experience, including recovering a reporting-critical Elasticsearch outage by standing up a new cluster in Kubernetes, restoring from snapshots, and rewinding Kafka consumers to reprocess missed data.”

Shweta Gupta

Screened

Senior Backend Software Engineer specializing in Java microservices, Kafka, and AWS

Seattle, WA6y exp

“AI engineer who shipped a production chat assistant for a storage company by building the underlying RAG-style knowledge base (document ingestion, chunking/embeddings, FAISS vector store) and an admin update interface to keep content current. Also has full-stack delivery experience (Python REST APIs + React/TypeScript UI) and AWS operations using Terraform/Jenkins, including handling a real production performance incident by optimizing DB queries and adding auto-scaling.”

“Platform/infrastructure engineer with hands-on ownership of Kubernetes, Terraform, VMware, and hybrid on-prem/AWS environments. Stands out for combining deep platform build/upgrade experience with strong incident response and reliability practices, including a Terraform redesign at H&R Block that reduced provisioning time by 40% and hybrid networking improvements that hardened Direct Connect failover.”

Michael Yeung

Screened

Mid-level Software Engineer specializing in FinTech trading platforms

San Francisco, CA4y exp

“Built and deployed internal trading tools at Wells Fargo that reduced manual production-support dependency for trader configuration workflows. Brings hands-on experience in financial systems, data quality, and production incident resolution, including building 400+ SQL validation rules and designing an internal RAG assistant for engineering documentation.”

Brendan Dwyer

Screened

Senior AI/ML Engineer specializing in GenAI and cloud platforms

Colorado Springs, CO10y exp

“ML/AI engineer with hands-on experience turning research-style RAG concepts into production underwriting systems at Prudential Financial. Built an internal document intelligence assistant end-to-end with strong monitoring, safety, and evaluation practices, driving a 38% faster review process and 31% better retrieval accuracy. Also improved platform engineering at VivSoft by standardizing Python-based ML deployment across 60+ models.”

“Full-stack engineer at an early-stage startup with hands-on production experience spanning Angular frontend features, backend safety checks for an image-generation workflow (OpenAI Safety), and AWS operations. Built CI/CD to ECS with GitHub Actions, implemented CloudWatch observability, and improved release reliability via Blue/Green deployments with automatic rollback.”