Western Digital
Data Storage
EngineeringDirector,AgenticAI
“Engineering Director, Agentic AI at Western Digital. Skills: Agentic AI Delivery, Autonomous AI Agent Systems, LLMs, GenAI, Distributed Systems, Cloud Infrastructure, MLOps, Technical Strategy, Leadership. Oversee multiple autonomous AI agent systems that interact with complex enterprise workflows, external APIs, and real-time data. Translate cutting-edge AI research into reliable, scalable, and secure production systems”
What You'll Achieve.
Timely delivery of agentic AI use cases; Reduced failure rates and hallucinations in production; Measurable business impact from deployed agents; High leadership satisfaction with transparency and predictability
Industry & Context.
Problem solvers; Optimize AI infrastructure for cost, latency, and performance
What They're Looking For.
Must Have
Hands-on experience designing and deploying autonomous AI agents, Deep knowledge of LLMs, GenAI, vector databases, embeddings, and prompt engineering, background in distributed systems, microservices, and cloud infrastructure (AWS/GCP/Azure), Experience with MLOps, observability, and AI security mitigation, executive communication and stakeholder management, Proven crisis management experience with autonomous systems, Strategic thinking to align technical execution with business goals
Nice to Have
0-8+ years in software engineering with 0-4+ years in leadership, Experience launching enterprise or consumer AI products, Background in RLHF or domain-specific LLM fine-tuning, Familiarity with AI regulatory frameworks (e. g. , EU AI Act, NIST AI RMF)
What You'll Do.
Oversee multiple autonomous AI agent systems that interact with complex enterprise workflows
Translate cutting-edge AI research into reliable
and secure production systems
Provide strategic clarity to executive leadership
Define and execute the technical strategy for multi-agent AI systems
Own delivery roadmaps for high-priority agentic AI use cases
and metrics to the C-suite
Allocate engineering resources across competing projects
Transition agentic prototypes to production with robust guardrails and fail-safes
Establish standards for reliability
Optimize AI infrastructure for cost
Ensure compliance with data privacy and security standards
Build and mentor high-performing teams of engineers and AI researchers
Collaborate with Product
and Security teams to define capabilities and constraints
Foster a culture of innovation while maintaining production reliability
How You'll Work.
Team & Collaboration
Collaborate with Product, Data Science, and Security teams to define capabilities and constraints
Communication Scope
Communicate progress, risks, and metrics to the C-suite; executive communication
Process & Methodology
Own delivery roadmaps, Allocate engineering resources across competing projects
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