Senior Systems Engineer, CoreAI - Agentic Solutions (Remote)

The Home Depot is a leading home improvement retailer, and they are seeking a Senior Systems Engineer within their CoreAI team. The role involves developing, maintaining, and supporting generative AI and agentic infrastructure, while collaborating with a team to architect scalable systems and ensure operational stability.

Responsibilities:

• Keeps abreast of innovations and industry trends as well as changes to internal systems and determines how they impacts tools, training, and support necessary to keep systems up, running, and secure; Participates in and contributes to learning activities around modern systems engineering core practices (communities of practice); Proactively views articles, tutorials, and videos to learn about new technologies and best practices being used within other technology organizations
• Keeps abreast of innovations and industry trends as well as changes to internal systems and determines how they impacts tools, training, and support necessary to keep systems up, running, and secure; Participates in and contributes to learning activities around modern systems engineering core practices (communities of practice); Proactively views articles, tutorials, and videos to learn about new technologies and best practices being used within other technology organizations
• Researches and analyzes business trends and behavioral data to identify opportunities for improvements and new initiatives; Drives the evaluation, development, and recommendation of specific technology to provide cost-effective solutions that meet THD requirements; Researches and designs best fit infrastructure, network, database, cloud, AI, and security architectures for products; Proactively creates and maintains tools for monitoring and support; Participates in project planning and reporting across multiple efforts
• Collaborates with product and project teams to understand needs and enable them with infrastructure; Supports technology architecture design review efforts for project and product teams; Leverages tooling and custom applications to monitor the operational status of applications, infrastructure, networks, databases, and security; optimizes and tunes performance as appropriate; Drives root cause analysis, debugging, support, and post-mortem analysis for security incidents and service interruptions; Maintains, upgrades, and supports existing systems and infrastructure to ensure operational stability; Opens and manages vendor problem tickets to resolution; Drives the production of in-house documentation around solutions; Provides application support for software running in production; Drives moving KB articles to infrastructure as code models; Drives keeping monitoring/alerting up to date

Requirements:

• Must be eighteen years of age or older
• Must be legally permitted to work in the United States
• Professional or educational experience as an Information Technology, Platform, or AI/MLOps Engineer, with a strong emphasis on applying first principles thinking to system design and troubleshooting
• Experience working as part of a collaborative, cross-functional, modern engineering team, including a proven ability to lead technical discovery sessions and present tailored architectural solutions to both technical (MLEs, developers) and non-technical business stakeholders
• Experience with scripting and programming, with mandatory strong proficiency in Python, Model Context Protocol (MCP), and building robust ADK agents. Familiarity with orchestration frameworks like LangChain or LlamaIndex is a plus
• Experience with cloud platforms, primarily GCP, with hands-on core engineering expertise in Vertex AI Agent Engine, Vertex AI Vector Search, and BigQuery
• Experience monitoring the operational status and performance of, and configuring as well as tuning, systems, networks, vector databases, and LLM telemetry (latency, token usage, cost)
• Familiarity with system and environment analysis, design, and optimization for enterprise-wide generative AI platforms, focusing on foundational engineering requirements like high availability, fault tolerance, and establishing AI governance and compliance guardrails
• Experience in troubleshooting and remediation within multiple Information technology disciplines, applying deep root-cause analysis to resolve complex agentic workflow and distributed system failures
• Experience installing and upgrading applications or databases and performing system maintenance for high-throughput ML/AI workloads
• Familiarity with debuggers, runtime analysis, library systems, compiled programming, and software update tools
• Experience supporting a 24x7 retail operation, understanding the immense scale, security, and reliability required for THD enterprise systems
• Experience with version control systems and CI/CD toolchains tailored for the deployment of ML models, AI agents, and microservices
• Experience with production system designs including Infrastructure as Code (e.g., Terraform), containerization (e.g., GKE), High Availability, and Performance monitoring
• Exposure to Site Reliability Engineering (SRE), including enforcing least-privilege IAM policies and securely managing auth tokens for AI service accounts
• The knowledge, skills and abilities typically acquired through the completion of a bachelor's degree program or equivalent degree in a field of study related to the job
• 4 years of work experience