Sr. Director of End-to-End AI Applications - Infinia

Overview

This is an incredible opportunity to be part of a company that has been at the forefront of AI and high-performance data storage innovation for over two decades. DataDirect Networks (DDN) is a global market leader renowned for powering many of the world's most demanding AI data centers, in industries ranging from life sciences and healthcare to financial services, autonomous cars, Government, academia, research and manufacturing.

  

"DDN's A3I solutions are transforming the landscape of AI infrastructure." – IDC 

  

“The real differentiator is DDN. I never hesitate to recommend DDN. DDN is the de facto name for AI Storage in high performance environments” - Marc Hamilton, VP, Solutions Architecture & Engineering | NVIDIA 

  

DDN is the global leader in AI and multi-cloud data management at scale. Our cutting-edge data intelligence platform is designed to accelerate AI workloads, enabling organizations to extract maximum value from their data. With a proven track record of performance, reliability, and scalability, DDN empowers businesses to tackle the most challenging AI and data-intensive workloads with confidence. 

  

Our success is driven by our unwavering commitment to innovation, customer-centricity, and a team of passionate professionals who bring their expertise and dedication to every project. This is a chance to make a significant impact at a company that is shaping the future of AI and data management. 

  

Our commitment to innovation, customer success, and market leadership makes this an exciting and rewarding role for a driven professional looking to make a lasting impact in the world of AI and data storage. 

Job Description

As the Director of End-to-End AI Applications, you will lead the design, development, and delivery of production-grade AI applications that power strategic customer use cases—from data ingestion and pipeline orchestration to inference, visualization, and decision automation.

 

This role requires a unique blend of deep technical expertise, product vision, and execution leadership across the full AI lifecycle. You will partner closely with Engineering, Product Management, Field Teams, and strategic customers to build scalable, reliable, and intelligent application layers on top of high-performance AI infrastructure.

 

This is a hands-on technical leadership role — where vision meets execution. You’ll champion the use of AI-native tools, automation frameworks, and platform integrations to reduce time-to-insight, accelerate delivery velocity, and drive tangible business outcomes.

Key Responsibilities

AI Solution Architecture & Delivery

• Define and own the architecture of full-stack AI applications—from data ingestion to model serving and feedback loops.
• Lead cross-functional teams to deliver end-to-end AI solutions across domains such as GenAI, Computer Vision, LLMOps, and Predictive Analytics.
• Build reusable frameworks, automation patterns, and reference architectures to accelerate solution delivery.
• Embed observability, testing, and governance into every layer of the AI pipeline.

Team Leadership & Strategic Alignment

• Build and lead a world-class team of AI architects, ML engineers, full-stack developers, and product owners.
• Define and track OKRs focused on delivery velocity, reliability, customer impact, and AI innovation.
• Drive a culture of experimentation, continuous learning, and automation-first thinking.

Customer Engagement & Business Impact

• Serve as the technical face of AI applications for strategic customers—translating complex problems into actionable, scalable solutions.
• Partner with Engineering and Product teams to align AI investments with business value.
• Participate in executive briefings, solution workshops, and proof-of-value engagements to drive customer success.

AI/ML Tooling & Operational Excellence

• Leverage cutting-edge AI development and deployment tooling—prompt engineering, vector databases, pipeline orchestration (e.g., Kubeflow, Airflow), and LLM fine-tuning platforms.
• Champion AI observability and model performance monitoring for real-time feedback and drift detection.
• Drive automation of MLOps workflows using CI/CD, feature stores, and scalable inference platforms (Triton, Ray, KServe, etc.).

Required Qualifications

• 12+ years’ experience building distributed systems or data-driven applications, with 8+ years in AI/ML application delivery.
• Proven success designing and delivering production-grade AI solutions, includ