AI Workbench Admin

DXC Technology

. Administer and maintain the AI Workbench platform across private, on-premise, hybrid, or cloud environments .

Posted 9/18/2026full-timeAshburn • Virginia • United StatesSeniorLead💰 $84,400 - $156,700 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in administering AI Workbench platforms across various environments, with a strong focus on security, user access management, and integration with cloud services. Proficient in managing AI agent lifecycles and supporting data workflows while ensuring compliance with governance and security standards.

Highest-signal resume keywords

AI Workbench AdministrationRAG ArchitectureAzure DevOpsKubernetesActive Secret Security Clearance

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Open Source AI ArchitectureRBACDocument IngestionVector DatabasesGenerative AIAI Agent ManagementCloud Platform OperationsData PrivacyIncident ResolutionPlatform Performance Monitoring

Soft Skills

CollaborationTroubleshooting

Tools & Technologies

Azure Open AI ServicesAzure PostgreSQLAzure Blob StorageServiceNowSAPSharePointKongDagsterArgo CDNVIDIA-based AI Infrastructure

Certifications & Qualifications

Master’s Degree in Computer ScienceMaster’s Degree in Information TechnologyMaster’s Degree in Data EngineeringMaster’s Degree in Artificial IntelligenceMaster’s Degree in Cybersecurity

Industry Keywords

Cloud OperationsDevOpsDataOpsAI/ML Platform SupportZero-Trust Architecture

Tech Stack

Tools & technologies

AWSAzureCloudCyber SecurityGoogle Cloud PlatformKubernetesOpen SourceOraclePostgresServiceNow

About the role

Key responsibilities & impact

Administer and maintain the AI Workbench platform across private, on-premise, hybrid, or cloud environments
Configure user access, role-based access control, tenant-level segregation, permissions, and platform security settings
Support onboarding of users, teams, agents, workflows, APIs, data sources, and LLM connections
Monitor platform health, availability, security, performance, usage, and operational metrics
Manage AI agent lifecycle activities including agent registration, configuration, deployment, versioning, and operational readiness
Support RAG-based retrieval layers, vectorized knowledge bases, document ingestion pipelines, and data preprocessing workflows
Coordinate with DevOps/DataOps teams to maintain CI/CD pipelines, infrastructure automation, deployment workflows, rollback processes, and environment configuration
Support integrations with ServiceNow, SAP, SharePoint, APIs, MCP registries, data sources, and private LLM services
Maintain governance controls for prompts, agents, workflows, data access, naming conventions, tagging, audit logging, and policy adherence
Collaborate with architects, engineers, testers, product owners, business analysts, security teams, and client stakeholders
Troubleshoot platform issues, analyze logs, and coordinate incident resolution

Requirements

What you’ll need

Must be a US Citizen with an active Secret Security Clearance
Strong experience working with open source AI architecture admin components including LiteLLM, Kong, Dagster orchestration, Langfuse, and AI search
Experience with RAG architecture, document ingestion, vector databases such as Milvus, Chroma, and Pinecone, knowledge bases, embeddings, and retrieval workflows
Knowledge of access control, RBAC, Entra ID, tenant segregation, identity management, and enterprise security administration
Experience with Azure DevOps (ADO) to deploy container images to the MCP registry
Understanding of Azure Open AI services, Azure PostgreSQL, Azure Blob Storage containers, and Azure Application Gateway
Understanding of Generative AI, Agentic AI, LLMs, private LLM deployments, AI agents, and prompt lifecycle management
Excellent working knowledge of cloud platforms such as Azure, AWS, GCP, or Oracle Cloud OCI
Experience with Kubernetes, Argo CD, containers, container orchestration, and platform runtime management
Understanding of data privacy, encryption, secure key management, data masking, data residency, and audit logging
Ability to monitor platform performance, troubleshoot issues, analyze logs, and coordinate incident resolution
Strong collaboration skills with architects, engineers, testers, product owners, business analysts, security teams, and client stakeholders
Preferred: experience with NVIDIA-based AI infrastructure, GPU farms, model inference services, or accelerated compute environments
Preferred: knowledge of API management, authentication, authorization, and secure integration patterns
Preferred: understanding of zero-trust architecture, OWASP Top 10, secure software delivery, and enterprise compliance frameworks
Master’s degree in Computer Science, Information Technology, Data Engineering, Artificial Intelligence, Cybersecurity, or a related field, or equivalent professional experience
10+ years of experience in enterprise platform administration, cloud operations, DevOps, DataOps, infrastructure operations, or AI/ML platform support
3+ years of experience supporting AI, ML, GenAI, LLM, RAG, or automation platforms preferred

Benefits

Comp & perks

Health insurance coverage
Dental insurance coverage
Vision insurance coverage
Employee wellness
Life insurance
Disability insurance
Retirement savings plan
Paid holidays
Paid time off
Flexible work arrangements supporting wellbeing, productivity, individual work styles, and life circumstances