Manager, AI Platform Engineering Location: Georgia (Remote) Work Arrangement: Fully Remote Employment Type: Full-time Salary: $140,000 – $240,000 annually (For California, Colorado, Connecticut, Rhode Island, Nevada, New York, Westchester County, Ithaca, and Washington residents; compensation may vary in other locations.) Bonus: Eligible for Success Sharing Bonus. Travel: Yes – Approximately 5%–20% overnight travel. Position Purpose: As a Manager, AI Platform Engineering, you will lead the development and evolution of our enterprise Generative AI platform, enabling scalable, secure, and high-impact AI capabilities across the organization. This role combines technical delivery leadership with strategic thinking, overseeing a team of engineers to build and operate GenAI platform services, agentic workflows, and multi-model orchestration. You will partner with product, data, legal, cybersecurity, and business stakeholders to translate AI use case needs into scalable, reusable platform capabilities that drive enterprise-wide adoption and efficiency. You will ensure alignment with security, privacy, and governance standards while enabling successful delivery and commercialization at scale. In addition, you will collaborate with strategic vendors and internal platform teams to accelerate innovation and support a growing portfolio of AI solutions. This role is critical to scaling AI adoption across the enterprise, balancing rapid innovation with operational excellence and responsible AI practices. Key Responsibilities: - 30% Delivery & Execution: - Collaborates and pairs with product team members (UX, engineering, and product management) to create secure, reliable, scalable software solutions - Documents, reviews and ensures that all quality and change control standards are met - Writes custom code or scripts to automate infrastructure, monitoring services, and test cases - Works with vendors and partners for the successful implementation of critical tooling and platforms - Creates meaningful dashboards, logging, alerting, and responses to ensure that issues are captured and addressed proactively - Contributes to enterprise-wide tools to drive destructive testing, automation, and engineering empowerment - Evaluates new technologies for adoption across the enterprise - Participates in and leads review board sessions to drive consistency across the enterprise - Fills in on product teams for engineers who are out of the office - 10% Support & Enablement: - Fields questions from engineers, product teams, or support teams - Monitors tools and participates in conversations to encourage collaboration across product teams - Provides application support for software running in production - Acts as a technical escalation point for the engineers on the team - 50% People: - Provides leadership, mentoring, and coaching to Software Engineers - Attracts, retains, and develops top talent to build a world class Software Engineering Team - Conducts annual and mid-year reviews by reviewing individual development plans and team feedback - Fosters collaboration with team members to drive consistency across product teams, and finds opportunities to expose engineers to career interests - Acts as a proponent of modern software development practices - Guides team members in strategy, alignment, analysis, and execution tasks within and across product teams - Participates in and contributes to learning activities around modern software design and development core practices (communities of practice) - 10% Learning: - Learns, through reading, tutorials, and videos, new technologies and best practices being used within other technology organizations - Builds relationships with technology leaders at other companies to learn best practices and elegant solutions to common problems Direct Manager/Direct Reports: - Typically reports to the Software Engineer Sr. Manager, Technology Director or Sr. Director. Travel Requirements: - Typically requires overnight travel 5% to 20% of the time. Physical Requirements: - Most of the time is spent sitting in a comfortable position and there is frequent opportunity to move about. On rare occasions there may be a need to move or lift light articles. Working Conditions: - Located in a comfortable indoor area. Any unpleasant conditions would be infrequent and not objectionable. Minimum Qualifications: - Must be eighteen years of age or older. - Must be legally permitted to work in the United States. - Mastery of an object oriented programming language (preferably Java) - Must be legally permitted to work in the United States Preferred Qualifications: - 8+ years of related work experience in software engineering, with at least 2 years focused on AI/ GenAI projects for large enterprises. - Experience with modern software delivery practices, including CI/CD pipelines, containerization, and orchestration technologies (e.g., Docker, Kubernetes), with a strong understanding of deploying and operating scalable, production-grade systems. - Experience designing or building AI agents and agent-based workflows, including orchestration of LLMs, tools, and external systems in production environments. - Strong understanding of AI, machine learning, and software engineering concepts, demonstrated through recent certifications or project experience - Proven track record of managing complex technical projects and leading junior engineering teams - Deep experience with ad tech, streaming media platforms, and digital content delivery - Familiarity with agile methodologies and project management tools (e.g., Jira, Trello, Monday) - Experience with cloud platforms (e.g. Azure, GCP) for scalable AI system deployment - Excellent problem-solving and analytical skills - Strong communication skills with ability to explain AI and software engineering concepts to both technical and non-technical audiences - Knowledge of privacy and security considerations in AI applications - Understanding of AI ethics and responsible AI practices - Strong leadership and mentoring abilities - Excellent interpersonal and team collaboration skills - Ability to think strategically about AI applications and their business impact - Proactive and self-motivated with a passion for emerging AI technologies and software engineering practices - Adaptable and able to thrive in a fast-paced, rapidly evolving AI and software development landscape. - Bachelor's degree in Computer Science, Software Engineering, or related field. Minimum Education: - 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. Preferred Education: - No additional education Minimum Years of Work Experience: - 5 Preferred Years of Work Experience: - No additional years of experience Minimum Leadership Experience: - None Preferred Leadership Experience: - None Certifications: - None Competencies: - Attracts Top Talent: Attracting and selecting the best talent to meet current and future business needs - Balances Stakeholders: Anticipating and balancing the needs of multiple stakeholders - Builds Effective Teams: Building strong-identity teams that apply their diverse skills and perspectives to achieve common goals - Business Insight: Applying knowledge of business and the marketplace to advance the organization's goals - Collaborates: Building partnerships and working collaboratively with others to meet shared objectives - Communicates Effectively: Developing and delivering multi-mode communications that convey a clear understanding of the unique needs of different audiences - Develops Talent: Developing people to meet both their career goals and the organization's goals - Drives Engagement: Creating a climate where people are motivated to do their best to help the organization achieve its objectives - Drives Vision and Purpose: Painting a compelling picture of the vision and strategy that motivates others to action - Manages Ambiguity: Operating effectively, even when things are not certain or the way forward is not clear - Organizational Savvy: Maneuvering comfortably through complex policy, process, and people-related organizational dynamics - Situational Adaptability: Adapting approach and demeanor in real time to match the shifting demands of different situations Benefits offered include health care benefits, 401K, ESPP, paid time off, and success sharing bonus. For a full list of the various benefits The Home Depot offers, visit https://careers.homedepot.com/our-benefits. For California, Colorado, Connecticut, Rhode Island, Nevada, New York City, Ithaca (NY), Westchester County (NY), and Washington residents: The pay range for this position is between $140,000.00 and $240,000.00

• Implement and integrate AIOps solutions across cloud and on-prem environments to enhance incident detection, correlation, and automated remediation. • Configure, manage, and optimize observability platforms (logs, metrics, traces) including ingestion pipelines, dashboards, alerting rules, and topology views. • Build automation workflows for operational tasks such as event triage, remediation actions, resource optimization, and predictive maintenance. • Collaborate with platform, cloud, and operations teams to onboard new services, data sources, and operational signals into the AIOps ecosystem. • Support deployment, integration, and operationalization of AI/ML models used for anomaly detection, event correlation, forecasting, and noise reduction (not model training). • Develop and implement playbooks, runbooks, and automated actions in line with SRE, DevOps, and cloud operations practices. • Troubleshoot issues related to observability ingestion, integration connectors, pipeline performance, and automation workflows. • Participate in architectural discussions, tool evaluations, and AIOps capability uplift initiatives. • Ensure compliance with security, governance, IAM, and data handling guidelines in the AIOps and observability ecosystem. • Document configurations, workflows, integrations, and operational guidelines for AIOps platform usage.

Role Description We're on the lookout for a skilled and motivated Azure Platform Engineer to join our cloud engineering team. This is a hands-on DevOps engineering role where you'll architect, automate, and operate Azure-based platforms that enable scalable, secure, and high-performance applications. You'll be instrumental in building cloud-native infrastructure using modern IaC principles, with a strong emphasis on automation, continuous integration/delivery, and observability. Responsibilities - Engineer solutions in Azure cloud, develop, and manage end-to-end Azure DevOps Pipelines (multi-stage YAML) for infrastructure and application deployments. - Automate Azure infrastructure using Azure Bicep, and manage deployments using GitOps and version-controlled CI/CD workflows in Azure DevOps Pipelines. - Design and deploy event-driven systems using: - Azure Event Grid - Azure Event Hub - Azure Functions - Provision and manage Azure Databricks clusters, notebooks, and workspace configurations. - Build pipelines for deploying custom Python libraries and microservices to staging and production environments. - Integrate and manage supporting services such as: - Azure API Management (APIM) for API gateway and policy configuration - Azure Key Vault for secrets, certificates, and identity integration - Azure Application Insights and Azure Monitor for performance and reliability monitoring - Log Analytics for observability and diagnostic analysis - Automate network provisioning: VNETs, subnets, private endpoints, NSGs, route tables, and firewalls. - Implement access controls, role-based access (RBAC), and security posture checks. - Collaborate across teams to embed DevOps best practices and ensure system resilience and compliance. Qualifications - Proficiency in Azure DevOps, YAML pipelines, release strategies, and artifact management. - Strong hands-on experience with Azure Bicep, ARM templates, or Terraform (Bicep preferred). - Expertise in automating and operating: - Azure Event Grid / Event Hub / Functions - Azure Databricks (incl. workspace automation & cluster management) - Azure Networking & Resource Groups - Working knowledge of Azure API Management, Key Vault, Application Gateway, and App Services. - Practical experience with deploying Python libraries and managing dependency versions across environments. - Strong scripting skills: PowerShell, Bash, or Python. - Familiarity with containerisation and orchestration (e.g., Docker, AKS, optional but desirable). - Good understanding of CI/CD, DevSecOps, and compliance in cloud environments. - Experience working with monitoring and logging tools like Azure Monitor, App Insights, and Log Analytics. Requirements - Azure certifications (e.g., AZ-400, AZ-104, AZ-305) - Experience with Service Bus, Storage Queues, or Event-Driven Architectures - Familiarity with GitHub Actions, Terraform Cloud, or Pulumi is a plus - Experience in FinTech, HealthTech, or regulated industries (for secure & compliant design) - Passion for automation, testing, and continuous improvement. - Ability to balance speed and stability in delivery. - Strong collaboration and stakeholder communication skills. - Desire to mentor others and share knowledge. - Committed to high standards of security, governance, and documentation. Other - Languages: English: C1 Advanced - Seniority: Senior

• Report to the PingOne Admin Experience engineering director. • Serve as a senior individual contributor on the PingOne Platform Administration team. • Participate in all stages of the software development life cycle, from requirements definition and technical design through implementation, testing, deployment, and production support. • Design and develop backend services and APIs that support the PingOne Platform Administration capabilities. • Contribute to the development of AI-related platform tooling, including MCP server capabilities, developer tools, and supporting workflows. • Partner closely with product managers, QA, UX, and peer engineering teams across PingOne to deliver high-quality solutions. • Help shape technical direction, engineering standards, and system design decisions within the team. • Mentor other engineers through design reviews, code reviews, and day-to-day collaboration. • Support operational excellence by improving observability, reliability, maintainability, and deployment safety of team-owned services.