Dhiraj Durgoji — CTO

I lead the technical execution of the AI roadmap for a 500+ person organization. Reporting directly to the VP of Engineering, I serve as the primary architect for our AI adoption strategy, ensuring that cutting-edge LLM capabilities are translated into scalable, production-ready tools. Core Impact: Organizational AI Frameworks: Leading a team of 8+ engineers to build the infrastructure that democratizes AI. This includes our Agent Orchestrator, which scaled to 100+ production agents in just 30 days, delivering immediate ROI across Dev, QA, and SRE teams reducing 1000+ hours of manual time saved every month. AI-Driven Quality: Developed an AI-based Code Review tool that automates complex logic checks and adherence to best practices, significantly reducing cycle time and improving codebase health. Adoption & Literacy: Acting as the internal subject matter expert, I drive the integration of tools like Claude and Copilot through strategic demos and trend analysis to maximize workforce efficiency. With a decade of experience in Kubernetes and distributed systems, I specialize in building AI infrastructure that is as robust as it is innovative. Previously (Before 2024) As a Full Stack Developer with a strong foundation in Backend, Frontend, DevOps, Testing, and People Management, I bring over a decade of experience in building robust, scalable applications and automation frameworks. I am passionate about creating high-performing software solutions and leading talented teams across diverse locations. End-to-End Development: Proficient in developing Machine Learning (ML) and Large Language Model (LLM) applications. Skilled in full-stack app development using Python, Django, Flask, JavaScript, and more. Automation Expertise: Extensive experience in designing and developing automation frameworks for Development and QA teams, including a custom unit test framework and a performance test framework based on Apache JMeter. Built a code coverage tool for internal languages and automation tools for streaming video playback on multiple devices. DevOps & Infrastructure: Skilled in containerizing infrastructure with Docker, orchestrating using Kubernetes and Docker Swarm, and setting up distributed execution for UI automation with Selenium Grids. Data Engineering: Hands-on experience in data scraping, cleaning, and analysis using Python and Apache Spark, including building solutions to handle large datasets. Infrastructure as a code: Automating cloud infrastructure with Terraform and Ansible for scalable, reliable, and repeatable deployments.

Stackforce AI infers this person is a SaaS-focused Principal Engineer specializing in AI infrastructure and full-stack development.

Location: San Francisco, California, United States

Experience: 13 yrs 5 mos