Principal Engineer, Software Development Engineering (Apps)

Company Description

Sandisk understands how people and businesses consume data and we relentlessly innovate to deliver solutions that enable today’s needs and tomorrow’s next big ideas. With a rich history of groundbreaking innovations in Flash and advanced memory technologies, our solutions have become the beating heart of the digital world we’re living in and that we have the power to shape.

Sandisk meets people and businesses at the intersection of their aspirations and the moment, enabling them to keep moving and pushing possibility forward. We do this through the balance of our powerhouse manufacturing capabilities and our industry-leading portfolio of products that are recognized globally for innovation, performance and quality.

Sandisk has two facilities recognized by the World Economic Forum as part of the Global Lighthouse Network for advanced 4IR innovations. These facilities were also recognized as Sustainability Lighthouses for breakthroughs in efficient operations. With our global reach, we ensure the global supply chain has access to the Flash memory it needs to keep our world moving forward.

Job Description

We are hiring a Principal Engineer to serve as an architect for Nexus, Enterprise AI platform for engineering workflows. This role partners with the existing platform architect to set technical direction across Nexus's hybrid on-prem and cloud architecture, lead design for agentic systems, MCP ecosystem, LLM gateway, memory and knowledge layers, and ensure the platform scales securely and reliably as adoption grows across FPG.

Essential Duties & Responsibilities:

• Architecture Leadership: Co-own end-to-end architecture for the Nexus platform across hybrid on-prem and cloud environments. Drive design decisions for agentic orchestration, MCP ecosystem, LLM gateway, memory and knowledge systems, observability, and platform applications.
• Technical Strategy: Define multi-quarter technical direction in partnership with engineering leadership. Translate platform vision into actionable architecture roadmaps that balance velocity, scalability, security, and operational maturity.
• Agentic Systems Design: Architect production-grade agentic workflows using LangGraph, Deep Agents, and modern agent frameworks. Establish patterns for tool use, multi-agent coordination, evaluation, and safety.
• Platform Standards: Establish and evolve standards for service design, API contracts, security, identity, observability, and developer experience across Nexus components and purpose-built applications.
• Cross-Functional Influence: Partner with InfoSec, Cloud Infrastructure, IAM, Networking, and product engineering teams. Lead architecture reviews, represent the platform in enterprise architecture forums, and shepherd designs through governance processes (ISAR, STARC, CAB).
• Technical Mentorship: Coach Staff and Senior engineers on system design, distributed systems, AI engineering, and production excellence. Raise the technical bar across the team through design reviews, code reviews, and architecture deep dives.
• Risk and Reliability: Identify architectural risks early, drive remediation, and lead the platform's evolution toward stronger environment separation, observability, and incident response maturity.
• Innovation: Track advances in LLMs, agentic frameworks, and AI infrastructure. Evaluate emerging technologies and lead targeted POCs that translate into platform capabilities.

Qualifications

Required:

• Master's or PhD in Artificial Intelligence, Machine Learning, Data Science, Computer Science, or a related field.
• 7+ years of professional software engineering experience, including 5+ years in architecture or technical leadership roles, with demonstrated impact designing and operating large-scale AI/ML, platform, or distributed systems in production.
• Deep proficiency in Python; strong working knowledge of TypeScript/JavaScript, React, and at least one systems language (Go, Java, or C++).
• Expert-level understanding of modern AI/ML stacks: LangGraph, LangChain, LlamaIndex, PyTorch or TensorFlow, and the Hugging Face ecosystem.
• Strong grasp of LLM internals, transformers, embeddings, RAG architectures, fine-tuning approaches, and evaluation methodologies.
• Production experience with LLM providers and gateways (Anthropic, OpenAI or equivalent), and deep familiarity with the Model Context Protocol (MCP) and agentic design patterns.
• Proven ability to design distributed systems, microservices, REST/GraphQL APIs, event-driven architectures, and high-throughput data pipelines.
• Strong experience with Kubernetes, Docker, and operating workloads in hybrid on-prem and