Mark Durante

Designing and building a local-first enterprise AI assistant that turns fragmented communications into connected knowledge and actionable insights. Combines graph database architecture and knowledge graph modeling with LLM-powered retrieval and synthesis and on-device embeddings. Connects conversations, topics, people, and tasks to surface relevant context, answer questions grounded in source evidence, and identify task ownership, priorities, and dependencies.

I lead architecture and engineering for Catspaw Systems, designing and operating cloud-based platforms that turn complex operational data into reliable, scalable software products. I initially architected and delivered distributed data ingestion and analytics pipelines for solar telemetry, using Python, Postgres, and AWS. This work replaced manual, error-prone workflows with automated software, scaling report generation from 6 solar sites per month to 36 sites per week, while improving accuracy, repeatability, and delivery timelines for stakeholders. I designed and implemented secure cloud infrastructure, including identity and access management using AWS Cognito, and established CI/CD and observability practices (structured logging, dashboards, alerts) to support production reliability and ongoing iteration. Deployments are fully automated using Bitbucket Pipelines and AWS tooling. More recently, I pivoted the company’s technical focus to a new product: a consumer-facing iOS trivia game. I am leading end-to-end development across the stack, including a SwiftUI-based iOS client and a backend built with Python, FastAPI, AWS Lambda, SQS, Postgres, and OpenAI APIs. This includes system design, implementation, and operational ownership. Across both efforts, I remain hands-on while setting technical direction, prioritizing work, and collaborating closely with partners to translate evolving requirements into durable, production-ready systems.

Recruit, develop and mentor engineering team both in-person and remotely; foster best practices in development, data engineering and DevOps ensuring high quality and availability. Lead by example, actively participate in code reviews, prototyping, bug fixing, and process efficiency improvements (CI/CD). Maintain product roadmap, ensuring technical feasibility given available resources and budget. Design and develop tools and microservices (AWS SAM in Python) for internal and external use. Present to technical and non-technical audiences: board, investors, customers, analysts, partners, sales, marketing. Author and maintain internal and customer-facing technical documentation. Manage $700,000 annual vendor budget. Own product data security, privacy and GDPR compliance.

Design, develop, maintain and enhance Text Analysis (NLP) component of SAP HANA, including build and test automation systems. Substantial work on parallelization and scalability.

Team lead and individual contributor for numerous IR and NLP libraries (C++), tools, and server products. Team lead responsible for eight engineers on search engine team during heavy push to expand feature set and increase performance and reliability of search subsystem; made key code paths thread-safe. Member of architecture team for charting longer-term technological strategies. Informal mentor to interns and junior engineers. Performed technical due diligence on company's mergers and acquisitions targets.