DDN is seeking an exceptional Senior Engineer to lead our Harness & Loop Engineering team within the Data Services Engineering organization. This role is responsible for building the internal engineering platforms, AI-powered development environments, inference infrastructure, and automated quality engineering systems that dramatically increase engineering productivity across the organization. The Harness platform serves as the foundation that enables small engineering teams to deliver with the velocity and effectiveness of much larger organizations while maintaining the highest standards of software correctness and reliability. As the technical leader for the Harness pod, you will define the architecture for AI-assisted engineering systems, guide the evolution of Loop Engineering practices, oversee inference orchestration platforms, and help transform internally developed capabilities into production-ready customer-facing products. This is a highly strategic technical leadership role requiring deep expertise in AI systems, large-scale distributed infrastructure, developer platforms, and software quality engineering. KEY RESPONSIBILITIES - Lead the architecture, technical direction, and execution of the Harness & Loop Engineering platform. - Design and build AI-powered development environments, agentic engineering sandboxes, automated quality engineering systems, and inference orchestration platforms. - Develop engineering platforms that significantly improve developer productivity while maintaining rigorous standards for correctness, reliability, and security. - Own technical architecture and provide final design and code review authority for AI-generated software changes. - Define evaluation frameworks, automated testing strategies, validation pipelines, and engineering guardrails that govern AI-assisted software development. - Partner closely with the Foundation SDK team to co-evolve platform capabilities and integrate emerging technologies into production-ready solutions. - Lead the evolution of internal engineering platforms into scalable, externally consumable products once validated through internal adoption. - Oversee internal GPU infrastructure, inference services, and Infinia cluster operations supporting AI development and testing environments. - Establish engineering best practices for Loop Engineering, agentic development workflows, and AI-assisted software delivery. - Mentor and develop engineers across the organization, raising technical standards through coaching, architectural guidance, and technical leadership. - Serve as a key technical interviewer and hiring bar-raiser for engineering talent. - Collaborate cross-functionally with software engineering, platform engineering, AI research, quality engineering, and product management teams to deliver scalable engineering capabilities. QUALIFICATIONS - Bachelor's degree in Computer Science, Computer Engineering, Software Engineering, or a related technical discipline; Master's degree preferred. - 12+ years of software engineering experience with demonstrated technical leadership in large-scale distributed systems. - Proven experience designing and delivering AI-assisted software development platforms or developer productivity tooling. - Demonstrated success using AI within correctness-critical software systems, including directing coding agents, automated quality engineering agents, and validating AI-generated outputs through rigorous evaluation frameworks. - Deep expertise in machine learning infrastructure, LLM inference serving, and distributed AI systems. - Strong experience building developer platforms, engineering tooling, and software automation frameworks. - Experience with agentic systems, inference orchestration, and AI workflow automation. - Hands-on experience managing GPU clusters, AI compute infrastructure, or large-scale distributed computing environments. - Strong understanding of software architecture, CI/CD pipelines, automated testing frameworks, and production software lifecycle management. - Proven experience mentoring engineers and leading highly technical engineering initiatives. PREFERRED - Experience productizing internal engineering platforms for external customers. - Knowledge of AI infrastructure management, model serving frameworks, and high-performance computing environments. - Experience with large-scale observability, platform reliability, and engineering operations. - Familiarity with storage systems, distributed data platforms, or enterprise AI infrastructure. - Contributions to open-source developer platforms, AI tooling, or infrastructure projects. TECHNICAL SKILLS - AI-Assisted Software Development - Agentic Engineering Systems - Loop Engineering - Developer Platforms & Tooling - LLM Inference Serving - Inference Orchestration - GPU Infrastructure & Cluster Operations - Distributed Systems Architecture - CI/CD Automation - Automated Quality Engineering - Software Validation & Evaluation Frameworks - Cloud & Container Technologies - Production Platform Engineering WHAT YOU'LL BRING - A passion for building engineering platforms that fundamentally improve how software is developed. - Exceptional architectural thinking with the ability to balance innovation, scalability, and operational excellence. - Strong technical judgment in evaluating AI-generated software within correctness-critical environments. - A collaborative leadership style with the ability to mentor engineers and influence technical direction across organizations. - A product mindset focused on transforming internal innovation into customer-ready capabilities.