AI Workbench Admin; Hybrid
Listed on 2026-09-21
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IT/Tech
Cloud Computing: Infrastructure & Operations, Cybersecurity, AI Engineer (Applied/Software), Azure
Job Description:
DXC Technology (NYSE: DXC) is a leading enterprise technology and innovation partner delivering software, services, and solutions to global enterprises and public sector organizations — helping them harness AI to drive outcomes at a time of exponential change with speed. With deep expertise in Managed Infrastructure Services, Application Modernization, and Industry-Specific Software Solutions, DXC modernizes, secures, and operates some of the world’s most complex technology estates.
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Must be a US Citizen with an active Secret Security Clearance
Work Environment:
Hybrid, on-site 2-3 days, Cristal City, Arlington, VA
Key Responsibilities
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 and support 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 Dev Ops/Data Ops teams to maintain CI/CD pipelines, infrastructure automation, deployment workflows, rollback processes, and environment configuration.
Support integrations with enterprise systems such as Service Now, 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.
Strong experience working with open source AI architecture admin components including LiteLLM, Kong, Dagster orchestration, Langfuse, AI search, etc.
Experience with RAG architecture, document ingestion, vector databases (Milvus, Chroma, Pinecone, etc.), knowledge bases, embeddings, and retrieval workflows.
Solid knowledge of access control, RBAC, Entra , tenant segregation, identity management, and enterprise security administration.
Experience working with Azure Dev Ops (ADO) to deploy the container images to the MCP registry.
Strong understanding of Azure Open AI services, Azure PostgreSQL, Azure Blob Storage containers, 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.
Experience with NVIDIA-based AI infrastructure, GPU farms, model inference services, or accelerated compute environments.
Knowledge of API management, authentication, authorization, and secure integration patterns.
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…
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