# Mark Zarutin > Lead Engineer| Python & Cloud | 4+ Years Building Scalable, AI-Integrated Systems Location: Brooklyn, New York, United States Profile: https://flows.cv/markzarutin 🤓 Psychology → Neuroscience → AI: My Unlikely Path to Building Tech That Feels Human I’ve always been obsessed with why we do what we do. At UCSB, I studied Psychology to understand human behavior. At NYU, I dove into Neuroscience to dissect how brains learn. Then I crossed over to code—because why simulate neural networks when you can build them? By the time I hit Columbia’s AI/Fintech program, I realized my niche: providing useful intelligence to those needing it. 💡 Why I’m Here I’ve closed the chapter at BrightBoundAI to do something much more important. Now, as the Lead Engineer at AskApe, I’m tackling scale and reliability, providing market intelligence never before seen in the hands of retail investors. I’m engineering fintech backends where instantaneous responses are always delivered with highest intelligence and drive profits. Here’s What I’ve Built (and Why It Matters): At Veo: Rewired backend systems for millions of users. Fixed geofencing code so your scooter actually unlocks where it should, and tripled test coverage. At StudyAI: Taught GPT-4 to teach any book to you like you are attending a class for it, but sales weren't my thing then, so down it went. At BrightBoundAI: Simplified an autonomous outreach stream for new startups, delivering new discovery calls in days. At AskApe: Heard people say a genuine thank you when they could suddenly afford to get their car fixed. ⚙️ My Happy Place Backend Challenges: If it involves Python, K8s, or battling Kafka streams at 2 a.m., I’m in. AI That’s Useful: LLMs that write sales emails? Cool. Intelligence that profits your community directly? Hell yes. 🌱 What’s Next? I want to work on tools that people don't yet know they desperately need. Think: AI portfolio manager that is accessible and useful to everyone. Gardening automation platform that can be DIYed by a 7 year old (may be projecting here) Personal/Health system that spreads like a religion 2000 years ago 🪴 When I’m Not Coding: Teaching my balcony garden to survive NYC summers with a Raspberry Pi and stubborn optimism Explaining to Alexa that “By the way…” is not a personality trait Debating whether emulating Windows 98 on a smart fridge counts as “edge computing” Let’s Chat If: Your backend needs someone who cares about why data flows and why it doesn't right now You’re building something that helps people first your employees second You want to rant about Docker, KV cache optimizations, token compression, or why vertical farms need better APIs ## Work Experience ### Founding Software Engineer @ Ape AI Jan 2025 – Present | New York, United States Leading a superb team of 5 engineers to make a resilient, comprehensive, and proactive trading/investing platform. Overseeing technical strategy, system stability, and making sure our clients have the best AI working tirelessly to make them money! ● Designed a Durable Execution framework to handle long-horizon AI workflows (e.g., multi-day earnings analysis). Enabled agents to survive infrastructure failures without state loss, ensuring high reliability for financial operations and research flows. ● Engineered a predictive KV-cache pre-filling system for multi-agent handoffs. Reduced Time-to-First-Token (TTFT) to 0ms and cut P50 agent latency from 2 minutes to <30 seconds via proactive context warming and tool batching. ● Architected a hybrid data layer, utilizing ClickHouse for high-frequency financial time-series data and Postgres for news and social data coalescing for most insightful and useful feed. ● Achieved a 10% MoM cost reduction by building a dynamic model router that optimizes for token economy. Implemented a closed-loop simulation pipeline (paper trading) to continuously benchmark AI trade ideas against real-market performance. ● Hardened the platform for brokerage integration by leveraging distributed secret management, immutable access audit trails, and strict PII minimization. ● Established a robust observability stack (Sentry, Distributed Tracing, PagerDuty) and introduced CI/CD pipelines with automated LLM regression testing, ensuring seamless zero-downtime deployments. ### Founding Engineer @ BrightBoundAI Jan 2024 – Jan 2025 | New York, New York, United States Architected and developed a B2B Generative AI platform from the ground up, focusing on backend engineering, AI integration, and cross-functional collaboration. Key achievements: ● Built a scalable Python/Django/Postgres backend with Docker, Redis, Celery, and REST APIs, automating lead generation workflows to process 10,000+ emails/day at 98% deliverability. Reduced operational costs by 85% to $0.01 per enriched lead through optimized resource allocation. ● Developed Generative AI models (LangChain, NLP, LLaMa, HuggingFace) to personalize email content and analyze lead behavior, driving 35% higher response rates and 160% more positive replies. ● Engineered a fully automated pipeline for lead discovery, enrichment, and outreach, focusing on background tasks for performance tracking and iterative campaign optimization. ● Achieved 80%+ code coverage via unit/integration testing (jUnit) and CI/CD pipelines, ensuring reliability and scalability for high-traffic workloads. ● Collaborated on product strategy and client onboarding. Ideal for teams seeking a backend-focused engineer with expertise in AI-powered systems, high-volume automation, and delivering measurable business impact through technical execution. ### Back End Engineer @ Veo Jan 2022 – Jan 2024 | Santa Monica, California, United States ● Restructured the geofencing system improving performance, removing redundancy, and standardize the user experience across company software. ● Led the efforts to improve memory performance and stability of the backend systems. ● Improved Veo-Access and Veo-Plus memberships while adding new functionality. ● Implemented internal suggestions to improve the experience of Veo workers when interacting with internal tools. ● Created multiple scripts and cron jobs for various bug fixes, and as testing of new functionalities. ### Co-Founder, Lead Backend Developer @ StudyAI Jan 2022 – Jan 2023 | New York, United States Co-created an educational platform that offered education on any topic, provided a knowledge base. Enabled the following functionalities: ● Given a book or video, created a teacher agent based on OpenAI GPT4 ● This teacher can teach you any concept from the material, ranging from specific questions to complex multilesson plans based on a generic inquiry. ● This teacher can create homework questions in multiple choice and long format. ● This teacher can edit and review your work, grade it, understand where mistakes came from and offer directions for improvement. ### Back End Developer @ Shoptaki Jan 2021 – Jan 2022 | New York, New York, United States ● Analyzed popular datasets with Pandas in search of common points of automation of raw data processing ● Created a data preprocessing agent using SciKit that learned from users becoming more autonomous ● Aided with visualization agent that automatically provided different graphs depending on the dataset ● Integrated both agents into the back end of ShopTaki demo website using Flask and set it up with AWS ### Back-end Developer @ Shoptaki Jan 2021 – Jan 2022 | New York City Metropolitan Area ### Research Assistant @ Landy Lab at NYU Jan 2021 – Jan 2021 | New York, New York, United States ● Reviewed and organized eye-tracking literature to present current methods of eye-tracking analysis ● Dissected and modified given datasets to find the vestibulo-ocular reflex during walking ● Developed eye-tracking algorithms for analysis and visualization of head-mounted eye movements ● Identified and reported on problems of the current head-mounted eye-tracking methodology ### Machine Learning Consultant @ NYU Bluestone Center for Clinical Research Jan 2021 – Jan 2021 | New York, New York, United States ● Created the framework for mice tracking and behavior analysis using transfer learning with DeepLabCut ● Developed the classification algorithm for differentiating qualifying behaviors under the project guidelines ● Trained research staff to use the framework and adapt it to their needs should changes arise ## Education ### Bachelor's degree in Neuroscience New York University Jan 2020 – Jan 2022 ### BootCamp in Fintech and Blockchain Columbia Engineering Jan 2021 – Jan 2022 ### Computational Neuroscience Neuromatch Academy Jan 2021 – Jan 2021 ### Psychology UC Santa Barbara Jan 2018 – Jan 2020 ### High School Diploma The Newman School Jan 2014 – Jan 2018 ## Contact & Social - LinkedIn: https://linkedin.com/in/markzarutin --- Source: https://flows.cv/markzarutin JSON Resume: https://flows.cv/markzarutin/resume.json Last updated: 2026-04-01