Jacob Kostenick

Director of Engineering

Overview

Jacob is a seasoned technology leader with hands-on expertise in developing data and AI architectures, cloud computing, and web development. Jacob brings a strategic mindset and a hands-on technical proficiency to every project, ensuring innovative, scalable, and efficient solutions for his clients.

His extensive experience in Azure, AWS and Snowflake allow him to bring creative solutions to clients on either side of the cloud space. He also brings a deep proficiency for C#, React and TypeScript, and excels at designing and implementing cutting-edge web solutions that drive business value. His ability to bridge the gap between complex technical challenges and critical real-world applications makes him a trusted advisor to many clients across multiple industries.

Based out of Bellingham, WA, Jacob is passionate about software engineering, personal fitness, movies, and electronic music.

Recent Insights

June 12, 2025

Closing the AI Access Gap for Small and Midsize Businesses

Kaigenix brings advanced, agentic AI to SMBs, offering affordable, tailored solutions that help smaller businesses stay competitive.
June 10, 2025

Kaigenix Redefines How Businesses Build with AI

Kaigenix turns data into action with adaptive AI, reducing costs and removing the need for large internal development teams.
June 10, 2025

Builder.ai’s Implosion: A Lesson in Startup Authenticity

Builder.ai’s collapse reveals the dangers of hype-driven tech. A cautionary tale about transparency, accountability, and real AI innovation.
June 10, 2025

AI Doesn't Threaten Your Job, But Ignoring It Might

Your job is safe if you evolve with AI. Harris Data Group helps teams integrate agentic AI to boost value and efficiency.
June 10, 2025

Responsible AI for High-Stakes Government Decisions

Harris Data Group builds ethical AI to support unbiased, strategic decision-making in diplomacy and global conflict resolution.
June 10, 2025

Trustworthy AI Begins with Transparent Data Sourcing

Harris Data Group addresses AI bias by building systems on balanced, vetted data to ensure ethical, accurate, and trustworthy outcomes.