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Vetted Observability Professionals
Pre-screened and vetted.
Mid-level Python Backend Developer specializing in cloud-native microservices and AI/ML platforms
Senior Software Engineer specializing in payments, billing, and fraud/risk platforms
Mid-level Software Engineer specializing in full-stack and distributed backend systems
Mid-level AI/ML Engineer specializing in LLMs, multilingual NLP, and low-latency MLOps
Executive CTO and serial founder specializing in AI platforms and Financial Services
Staff Software Engineer specializing in secure cloud-native data platforms
Senior Software Engineer specializing in autonomous driving and FinTech systems
Senior Software Engineer specializing in distributed systems and e-commerce platforms
Senior Software Engineer specializing in AI-powered FinTech infrastructure
Staff AI Platform Engineer specializing in enterprise SaaS and cloud AI systems
Senior Full-Stack & AI/ML Engineer specializing in cloud-native SaaS and IoT analytics
Senior Cloud Engineer specializing in AWS/Azure infrastructure, DevOps, and cloud-native platforms
Principal/Staff Engineer specializing in platform architecture, AI/ML, and distributed systems
Mid-level Software Engineer specializing in backend and distributed systems
Director-level Engineering Leader specializing in FinTech and distributed systems
Thazim Banu Shaffee
Engineering Manager specializing in payments, risk, and high-scale distributed systems
“Engineering leader/player-coach on a risk core transaction platform (payments/branded checkout) who led major migrations from a monolithic stack to microservices, including API contract redesign and performance improvements (reported ~500ms latency reduction). Experienced running high-stakes production incidents (upgrade-related outage/degradation) end-to-end with RCA and rollout-process changes, and has accelerated delivery via documentation/tooling (audit sign-off cycle reduced from ~3 sprints to ~1).”
Jared Alessandroni
Executive CTO specializing in AI, cloud platforms, and scaling SaaS products
“NYC-based startup founder/CTO who sold products to Omnicom and Sprinklr, then built an AI-powered cultural insights engine inside Omnicom using AWS Lambda + ML to process ~1M items/day and reached ~$1MM ARR in year one. Former senior leader at Sprinklr managing 200+ people globally, delivering enterprise martech solutions with SLAs and high-reliability social data pipelines (Twitter firehose).”
Abhijay Sai Paladugu
Junior Data Scientist specializing in LLM agents, RAG, and reinforcement learning
“McKinsey practitioner who built and deployed production LLM systems for consultants/clients, including a Power BI-integrated multi-agent chatbot (RAG + text-to-SQL + formatting) with custom Python orchestration, verification loops, and a 100+ case eval set achieving ~95% consistency. Also delivered a taxonomy-mapper agent that standardized inconsistent labeling for C-suite stakeholders, cutting a process from >2 weeks to <30 minutes through demos and business-focused communication.”