Digital Realty

AI Engineer

• Build and maintain backend services using Azure Functions, Semantic Kernel, LangChain/LangGraph/AutoGen/CrewAI.
• Develop APIs to orchestrate LLM workflows, manage state, and support chat and analytics front ends.
• Implement multi-agent pipelines with planning, reasoning, and execution flows.
• Design and manage RAG pipelines (chunking, embedding, indexing, hybrid retrieval) and extend retrieval with GraphRAG and entity-driven reasoning.
• Build ingestion pipelines to validate, clean, and test data before adding it to the AI knowledge layer; integrate data from CosmosDB, Dataverse, APIs, Azure Cognitive Search, SharePoint, and other enterprise sources.
• Create automated evaluation methods for retrieval accuracy, hallucination, and dataset quality.
• Collaborate with front-end engineers to define API contracts, payloads, session flows; provide reusable backend services, SDKs, and documentation aligned with React/Next.js and shadcn frameworks.
• Implement telemetry, logging, and metrics (OpenTelemetry, Prometheus, Grafana); enforce RBAC, compliance, data masking/sanitization/lineage; optimize performance, latency, and token usage with robust error handling and scalable design.

Senior AI Engineer

Operations

• Execute all aspects of data center operations including operation, maintenance and repair of mission critical equipment and systems to achieve 100% uptime and 100% compliance with customer SLAs
• Supervise all construction activity and installations to ensure system design, installation and testing adhere to operational standards
• Witness testing of all equipment during commissioning and validate sequence of operations and receipt of operational documentation
• Manage provisioning of data center services including colocation, connectivity, raised floor services, deployment and additional services for customers
• Manage local customer installations in coordination with Sales Engineering, Design & Construction and Colocation Operations for move-ins, power circuit installations and connectivity
• Oversee local installation, maintenance and repair of all network infrastructure supporting Digital Realty and customer connectivity
• Supervise local engineering team to ensure adherence to standard operating procedures, sequence of operations and maintenance standards
• Develop, implement and audit local standard operating procedures, sequence of operations and maintenance standards
• Supervise local change management processes including review and approval of Method of Procedures (MOPs)
• Manage maintenance and repair contracts and ensure vendor compliance with performance standards and scopes of work
• Ensure timely execution of data center services such as remote hands, customer installations and service requests
• Supervise security personnel and manage security systems and compliance programs
• Act as primary technical and operational contact for data center customers and local point of escalation during emergencies and day to day operations
• Manage technical and operational incidents including emergency response procedures, resource coordination, customer communication, root-cause analysis and post event remediation
• Identify trends and analyze risks; track operational metrics and provide Senior Management oversight and long-term trend analysis
• Identify process based improvements that generate operational and financial efficiencies and develop business cases
• Support Property Manager with management of expenses, budgeting, forecasting and reporting by providing capital and expense requirements and justifications
• Support pre-sales process including conducting sales tours and reviewing lease proposals and agreements for compliance
• Support accreditation initiatives (SSAE16, SOC2, ISO 27001) as required
• Maintain compliance with local health & safety standards and national electrical and building codes

Data Center Operations Manager

General Counsel

• Draft, negotiate and review agreements for data center space/power and ancillary services, including complex, multi-tiered and multi-jurisdictional customer master service agreements, individual leases, colocation licenses, service agreements and other occupancy agreements, orders, addenda or amendments for ancillary services.
• Provide legal support to portfolio management and property operations teams related to datacenter customers, including day-to-day matters (tenant inquiries and audits) and more significant projects.
• Support the continuous improvement of standard forms and the development and improvement of policies and procedures for the Legal Department.
• Help evaluate legal strategy with respect to datacenter customers and identify and mitigate risk in the commercial environment.
• Work closely with the business to streamline negotiations and remove barriers to execution to achieve business goals while thoughtfully balancing risk.
• Execute assigned projects, including the development and implementation of processes, as determined by the needs of the Legal Department.
• Manage outside counsel effectively and efficiently.
• Report to the leader (Vice President, Associate General Counsel) of the Legal Commercial team in North America.

Senior Manager, Legal Counsel

Sales

• Create, manage and grow Digital Realty Channel and Alliance partnerships and collaborate with partners.
• Bring day-to-day leadership and structure to partner efforts and develop areas of collaboration.
• Develop, qualify and nurture sales opportunities for execution or hand-off to dedicated sales resources.
• Develop overall partner sales strategy aligned with Digital Realty’s Global Channels and Alliances To Market.
• Manage partner and DLR relationships and develop demand generation, sales enablement tools, and KPIs with Partner Marketing and Regional Partner network.
• Develop and manage sales opportunities and continually assess and refine joint value proposition and go-to-market models to drive effectiveness and results.
• Digital Realty supports enterprises and service providers with data center, colocation and interconnection solutions via PlatformDIGITAL® (global footprint).

Director, Channel Sales

Customer Success Manager

• Assist with CRM migrations & Integrations for M&A activities.
• Manage cross-functional business stakeholders and drive salesforce automations and processes to improve operational efficiencies.
• Manage SFDC admins, developers, and 3rd party resources across the globe and work closely with Peers and management in USA.
• Work with our institutional management team to establish suitable processes to support administrative, development, and change management activities.
• Define data retention policies and maintain the clean Salesforce.com platform.
• Ensure the platform licensing guidelines are in place from time to time, especially with APIs.
• Maintain lead, account, contact, contract, and opportunity records as needed by end users and for development projects within storage limits.
• Work with third-party integrations to Salesforce (experience with Marketo, DemandBase, LeanData, Sales Navigator, DocuSign, Conga CPQ, Conga Document Generation a plus).
• Complete regular internal system audits and prepare for upgrades.
• Keep up to date on new Salesforce features and Releases.
• Publish monthly release notes to users.
• Contribute towards technology roadmaps (build) while managing day to day SFDC operational needs (run).

Salesforce CRM Manager, Sales Cloud

Software Engineer

• We are seeking a visionary and technically elite Director of AI Solutions & Engineering to lead the architecture, engineering, and delivery of enterprise-grade AI solutions within our Corporate Data Office and AI team.
• This role blends deep technical expertise, strategic leadership, and hands-on engineering to deliver next-generation AI applications that leverage the full power of Artificial Intelligence, Machine Learning, and Data Science.
• You will own the end-to-end architecture and development of AI systems—leveraging the Microsoft Azure stack (Semantic Kernel, Azure Functions, Cosmos DB, Azure AI Search), React-based front ends, advanced evaluation and observability frameworks, and integrated ML workflows.
• The ideal candidate is a full-stack AI technologist fluent in AI-assisted development tools, capable of designing scalable architectures, leading engineering execution, embedding machine learning experimentation into the build process, and driving data science–driven insights into business solutions.
• What you'll do
• AI Architecture & Engineering Leadership
• Define and own the enterprise AI architecture blueprint to support Retrieval Augmented Generation (RAG), AI agents, machine learning pipelines, and multi-modal AI solutions.
• Architect and implement end-to-end AI applications using Azure Semantic Kernel, Azure Functions, Cosmos DB, Azure AI Search, and modern front-end frameworks (React/Next.js).
• Lead integration of AI solutions with enterprise data sources, APIs, and secure cloud/on-prem environments.
• Design high-availability, secure, and compliant AI systems aligned to enterprise standards.
• Machine Learning & Data Science Integration
• Oversee ML model lifecycle management from feature engineering and model training to deployment, monitoring, and retraining.
• Direct data science initiatives that use predictive modeling, NLP, and statistical analysis to inform and optimize business processes.
• Guide teams in experiment design, A/B testing, and model performance analysis.
• Ensure ML/AI models are explainable, ethical, and auditable, aligning with governance and compliance requirements.
• Full Stack AI Development
• Direct and contribute to development across the full stack—from prompt engineering and orchestration to data pipelines, model integration, and UI/UX.
• Build AI evaluation frameworks with automated testing, benchmarking, and real-time performance monitoring.
• Implement AI Observability solutions for accuracy, latency, drift detection, hallucination monitoring, and bias detection.
• Integrate AI FinOps practices to measure, manage, and optimize AI infrastructure costs.
• AI Tooling & Automation
• Champion the use of AI-assisted coding, testing, and documentation tools to maximize team productivity.
• Leverage n8n and similar workflow automation platforms to orchestrate AI pipelines and integrate with business processes.
• Continuously evaluate and adopt cutting-edge AI frameworks, SDKs, and cloud-native services.
• Technical Strategy & Stakeholder Engagement
• Partner with product, engineering, and business leaders to define AI/ML roadmaps, project priorities, and success metrics.
• Communicate architectural decisions and technical trade-offs to C-level executives and technical teams alike.
• Lead AI engineering and data science standards, governance, and best practices across the organization.
• What you’ll need
• Required
• Bachelor’s or Master’s degree in Computer Science, AI/ML, Data Science, or related field; PhD preferred.
• 8+ years of experience in AI/ML engineering, software architecture, or enterprise solution delivery, including at least 3 years in a leadership role.
• Proven track record architecting and deploying AI solutions at scale using Azure cloud services (Semantic Kernel, Functions, Cosmos DB, Azure AI Search, Azure OpenAI).
• Expert in full-stack development, including front-end (React/Next.js), backend APIs, and cloud-native architectures.
• Strong proficiency in machine learning frameworks (TensorFlow, PyTorch, scikit-learn) and experience with NLP, RAG, and AI agent development.
• Proficiency in AI orchestration frameworks (Semantic Kernel, LangChain) and AI evaluation/observability platforms.
• Experience integrating vector databases and graph databases into AI/ML solutions.
• Hands-on experience with AI workflow orchestration tools like n8n, Airflow, or Prefect.
• Demonstrated experience applying data science methodologies to business problems.
• Experience implementing AI cost optimization (AI FinOps) and observability practices.
• Preferred
• Experience in multi-agent AI systems, reinforcement learning, or generative AI product delivery.
• Familiarity with CI/CD pipelines, containerization (Docker/Kubernetes), and modern DevOps practices.
• Knowledge of security, compliance, and ethical AI considerations for enterprise deployments.
• Exceptional communication skills, capable of influencing technical and non-technical audiences.

Director of AI Solutions & Engineering

Manager

• Oversee the design, implementation, and maintenance of reliable infrastructure and services.
• Collaborate with other teams to define requirements, standards, and best practices.
• Identify and address performance bottlenecks and ensure system stability.
• Implement and improve monitoring and observability frameworks.
• Manage on-call rotations and incident response to minimize downtime and ensure swift resolution.
• Drive automation efforts to reduce manual tasks and improve efficiency.
• Implement structured engineering and operations processes.
• Analyze and evaluate existing processes to identify opportunities for improvement.
• Develop and implement the long-term reliability strategy for the organization.
• Make decisions about build vs. buy for tools and technologies.
• Ensure alignment with business goals and customer expectations.
• Manage relationships with vendors and other stakeholders.
• Act as a bridge between technical teams and other departments.
• Represent the SRE team to stakeholders and communicate effectively.
• Collaborate with other engineering teams to ensure efficient workflows.
• Foster a culture of blameless postmortems and continuous learning.