Vetted Incident Response Professionals

Pre-screened and vetted.

SP

Mid-level Software Engineer specializing in cloud infrastructure and AI systems

3y exp
Specra.AIGeorgia Tech
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ST

Senior Site Reliability Engineer specializing in multi-cloud, Kubernetes, and observability

Stamford, CT9y exp
Vanguard
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Anand Madhusoodanan - Executive HR Tech & Salesforce Architect specializing in AI-driven recruiting automation in Bengaluru, India

Executive HR Tech & Salesforce Architect specializing in AI-driven recruiting automation

Bengaluru, India9y exp
Taylor RecruitGeorgia Tech

Co-founder of an HR tech startup who took an LLM-centered skill intelligence engine from prototype to production to deliver explainable, skill-based resume insights as an alternative to black-box ATS screening. Previously worked in consulting (Deloitte, Stand Up, Brilio), with experience in technical demos/workshops, pre-sales scoping, and supporting large deal cycles (including a ~$1M UK automotive client).

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HK

Mid-level Full-Stack Software Engineer specializing in cloud and data platforms

Boston, MA5y exp
Northeastern UniversityPenn State University

Full-stack engineer with experience spanning Amazon IMDb and Northeastern’s NeuroJSON portal, combining consumer product work with complex scientific data applications. Built IMDb’s streaming providers feature—described as the company’s most impactful feature of 2023—and has hands-on experience with React/Angular, GraphQL, AWS, Python services, and production monitoring.

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PP

Intern Software Engineer specializing in distributed systems and security

San Jose, CA6y exp
AnyLogUniversity of Pennsylvania

Built a production LLM-powered analyst assistant at Discern Security to speed up SOC investigations using a RAG pipeline over security vendor documentation (Python PDF ingestion, vector search). Demonstrates deep, security-critical LLM engineering: structure-aware chunking with custom table parsing, grounded/cited responses, prompt-injection defenses, and post-generation validation, validated via golden datasets and adversarial testing; tool is used daily by analysts.

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SA

Mid-level Full-Stack Software Engineer specializing in FinTech and payments platforms

Texas, USA4y exp
PayPalNortheastern University

Worked on payments and wallet transactions, with an emphasis on observability and root-cause analysis. Delivered end-to-end A/B testing optimization and implemented Jenkins-based CI/CD automation that reduced manual implementation to 35% and cut deployments to ~2 minutes, with attention to operational considerations like on-call/call rotations.

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RC

Richard Cerow

Screened

Director of Marketing Technologies specializing in scalable web platforms for gaming

El Segundo, CA19y exp
KraftonUniversity of Notre Dame

Player-coach engineering leader focused on consumer-grade video/multimodal products and high-reliability identity/auth experiences. Led design and implementation of multi-step mobile login/MFA flows with telemetry-driven funnel improvements, shipped Node services and security fixes, and owned auth incidents end-to-end using RUM and step-level instrumentation. Introduced feature-flagged delivery and targeted review/testing practices to speed iteration ~20–30% while keeping login stability high.

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SV

sai venkata

Screened

Senior Data Engineer specializing in cloud lakehouse and real-time streaming pipelines

Texas, USA6y exp
CVS HealthUniversity of Central Missouri

Senior data engineer with experience in both healthcare (CVS Health) and financial services (Bank of America), building large-scale Azure lakehouse pipelines (30+ EHR sources, ~5TB) and real-time streaming services (Event Hubs/Kafka) for patient vitals. Strong focus on reliability and data quality (Great Expectations, monitoring/alerting, schema drift automation), with measurable outcomes like 50% runtime reduction and 99%+ uptime for regulatory reporting pipelines.

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Akhil Kunala - Mid-level Software Engineer specializing in backend systems and cloud-native FinTech in Seattle, WA

Akhil Kunala

Screened

Mid-level Software Engineer specializing in backend systems and cloud-native FinTech

Seattle, WA5y exp
AmazonUniversity of North Texas

Amazon engineer with 5+ years of experience who built an AI-assisted log investigation and triage workflow that cut debugging time by about 30% during on-call incidents. Combines observability tooling like CloudWatch and Splunk with Python, prompt engineering, and RAG-based diagnostics, and has practical experience orchestrating agentic AI workflows with a strong human-in-the-loop reliability focus.

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SK

Sameen Kashfi

Screened

Executive Operations & PMO leader specializing in scaling FinTech, SaaS, and eCommerce organizations

15y exp
Eastern Asset ManagmentGeorge Mason University

Strategy & operations leader with senior roles at OnDeck, BlockFi, and Protocol Labs who owned founder-level initiatives end-to-end. Notably launched the first crypto credit card, driving 150k first-year sign-ups (vs 30k target) and boosting adoption of other offerings, and later cut time-to-hire from ~6 months to ~6 weeks while rebuilding GTM and operating frameworks.

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PP

Mid-level Cloud Support Engineer specializing in AWS microservices and payments APIs

Anaheim, CA4y exp
StripeCalifornia State University, Fullerton

Customer-facing technical support/solutions professional with experience at Stripe and Intuit helping developers take payment API and webhook integrations from testing to production. Uses Datadog and AWS CloudWatch to diagnose real-time production issues (e.g., webhook signature validation errors causing retries/delays) and unblocks customer deployments through hands-on, developer-oriented guidance.

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Kunal Singh Pundir - Mid-level Full-Stack Developer specializing in cloud microservices and GenAI systems in USA, USA

Mid-level Full-Stack Developer specializing in cloud microservices and GenAI systems

USA, USA5y exp
UberNortheastern University

Built and owned an end-to-end AI-driven decisioning platform at Uber, combining LLM orchestration with typed tool contracts and a Snowflake-based RAG pipeline to make decisions fully auditable. Delivered large-scale measurable impact (120k requests/day, 18k cases auto-resolved/month) while improving ops SLA from 3 days to 6 hours and cutting incident response time nearly in half. Previously led a high-risk strangler-fig modernization of a legacy insurance platform across 120+ microsites at Accenture, coordinating across multiple squads with feature-flagged parallel cutovers.

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Lamar Petty - Mid-level Full-Stack Product Engineer specializing in data-driven web apps and healthcare systems in San Francisco, CA

Lamar Petty

Screened

Mid-level Full-Stack Product Engineer specializing in data-driven web apps and healthcare systems

San Francisco, CA13y exp
Wikimedia FoundationGeorgia Tech

Full-stack engineer with production experience shipping a healthcare-focused web app (Pregnancy-Pal) using Next.js/TypeScript on GCP, integrating a Python/Flask middleware and FHIR server for patient/practitioner dashboards and messaging. Former Wikimedia Foundation Android engineer who led the end-to-end 'Year in Review' feature and built robust automated testing/CI practices (Espresso, GitHub Actions matrix). Strong emphasis on reliability via rigorous validation, comprehensive Postman testing, and detailed API documentation.

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MS

Manvir Singh

Screened

Senior Full-Stack & Mobile Software Engineer specializing in cloud-based applications

Englewood, NJ10y exp
Cobalt BrandsUniversity of Washington

Data/ML backend engineer with hands-on production experience spanning RAG services (LlamaIndex/OpenAI) and AWS data platforms. Has delivered Terraform-managed AWS architectures (Lambda + ECS Fargate) with secure secrets handling, built Glue-to-Redshift ETL with schema evolution controls, modernized SAS reporting into Python microservices, and achieved major Redshift query speedups (2+ hours to under 15 minutes).

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SM

Mid-level Full-Stack Developer specializing in Java/Spring Boot, React, and cloud-native AI automation

Long Beach, CA3y exp
UberCalifornia State University

Software engineer focused on reliability and scalable systems: built React/TypeScript dashboards backed by Java/Spring Boot APIs and designed Kafka-based microservices with strong contract/versioning discipline. Known for shipping incremental improvements with tight feedback loops and for creating internal observability tools that streamline on-call and incident diagnosis under high-traffic conditions.

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LL

Ling Lok Ngai

Screened

Mid-level Backend Software Engineer specializing in search infrastructure and AWS microservices

Fremont, CA6y exp
AmazonInternational Technological University

Search/backend engineer with hands-on experience improving Apache Solr-based search systems end-to-end (indexing strategy changes, ETL updates, and Java/Spring Boot Search API work). Demonstrated production rigor with QA partnership, A/B testing, and rollback-safe kill switches, plus measurable product impact (e.g., +1.5% add-to-cart) and operational troubleshooting including traffic/security mitigation.

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ZS

Zaki Sediqyar

Screened

Senior Technical Support Engineer specializing in platform escalations across FinTech and FAANG

San Francisco, CA9y exp
CoinbaseBerkeley City College

Customer support professional with Scrum Master and Product Owner certifications who has handled high-stakes account security incidents (including locking down an account to protect over $200k) and troubleshot live data feed integrations (XML/socket) by identifying IP whitelisting mismatches. Emphasizes transparent stakeholder communication, escalation, and building internal wiki documentation to prevent repeat issues.

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PN

Mid-level Full-Stack Engineer specializing in scalable APIs, cloud infrastructure, and GenAI apps

San Francisco, CA6y exp
DoorDashCal State Chico

Backend/platform engineer with experience across edtech, logistics, and AWS internal systems—owned a production course recommender end-to-end (model serving + APIs + caching/observability), delivering +30% CTR and -20% latency. Has scaled real-time delivery visibility/rerouting on Kubernetes/EKS to sub-200ms P95 during demand spikes and built billion-events/day telemetry pipelines on AWS (Kinesis Firehose, Lambda, S3, Redshift) with schema evolution, dedupe, and replay support.

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AK

Akshay Koneti

Screened

Mid-Level Full-Stack Software Engineer specializing in AWS cloud and microservices

Dallas, TX6y exp
AmazonUniversity of North Texas

Backend/LLM engineer who built a production-critical Amazon Bedrock + RAG correction and compliance layer for employee communications, integrating tightly with existing Spring Boot/AWS microservices to reduce manual review while keeping outputs explainable and auditable. Also designed an event-driven system processing 10M+ events/day (SQS/Lambda/DynamoDB/Elasticsearch) and handled on-call incidents with strong observability and reliability patterns (idempotency, retries, hotspot mitigation).

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SP

Mid-level Backend Software Engineer specializing in Python APIs and payment systems

USA6y exp
StripeSouthern Illinois University Carbondale

Backend/ML systems engineer with Stripe payments experience who built an asynchronous processing upgrade handling millions of API requests, cutting peak latency ~20–25% while preserving strict financial consistency via idempotency-safe retries and robust validation/fallbacks. Also built scalable ETL pipelines for messy CSV/Excel/API data with strong observability (structured logging/monitoring) and reliability mechanisms.

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Jignesh Desai - Director of Software Engineering specializing in fraud detection and payments platforms in San Francisco Bay Area, California, USA

Jignesh Desai

Screened

Director of Software Engineering specializing in fraud detection and payments platforms

San Francisco Bay Area, California, USA26y exp
VisaKennesaw State University

Engineering manager/player-coach who focuses on laying technical foundations and improving team execution: kickstarted Visa standard UI library adoption, standardized API exception handling, and introduced a test automation framework that enabled a shift from quarterly to monthly releases. Led a phased latency/throughput initiative that doubled throughput, and owned a production incident caused by a dependency’s expired certificate, driving monitoring and certificate-expiry notification improvements across dependent systems.

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Krishna Guda - Principal Product Engineer specializing in FinTech platforms, experimentation, and AI workflows in Mountain View, CA

Krishna Guda

Screened

Principal Product Engineer specializing in FinTech platforms, experimentation, and AI workflows

Mountain View, CA24y exp
Credit SesameBITS Pilani

Fintech product engineer working on a large-scale credit monitoring platform (tens of millions of users) with deep experience in regulated banking integrations, PII security, and step-up/MFA flows. Has shipped customer-facing React/TypeScript experiences driven by Optimizely experimentation and built reliable partner-facing microservices/SDKs on AWS, including resolving production traffic loss caused by edge security (DataDome/CAPTCHA) conflicts with payment providers.

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Shyaam Sundhar Rajamadam Srinivasan - Director-level Cybersecurity Architect specializing in cloud security, threat detection and incident response in Reston, VA

Director-level Cybersecurity Architect specializing in cloud security, threat detection and incident response

Reston, VA18y exp
Fannie MaeAmerican Military University

Entrepreneur building an AI-enabled platform to help tradespeople (e.g., plumbers/carpenters) find customers, currently moving from ideation toward MVP and user launch. Previously founded Votimo (2012), an early philanthropy/donation-transparency platform, raised ~ $2M in angel funding, and implemented the system before strategic drift from leadership/vision changes.

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Abraham Musa - Senior Solutions Architect specializing in cloud AI infrastructure and security in Union City, NJ

Abraham Musa

Screened

Senior Solutions Architect specializing in cloud AI infrastructure and security

Union City, NJ9y exp
FreelanceRutgers University

Cloud-native architect focused primarily on AWS, with experience designing Kubernetes and AI/ML infrastructure for customers rather than owning day-to-day operations. Particularly interesting for AI platform roles: they described using Amazon Bedrock to analyze Terraform and automatically generate compliant IaC templates and runbooks for new multi-cloud AI environments.

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