OpenAI Architect

- OpenAI Delivery: - Manage ChatGPT Enterprise deployment and governance: Plan workspaces, implement SSO/SCIM, create role models and policy guardrails; establish usage analytics; define custom GPT governance (actions/connectors, approvals) and runbooks. - Design OpenAI API architecture: Create patterns for Assistants with multi-tool orchestration, structured outputs (JSON schemas), function/tool calling, Files/Batch for bulk jobs, moderations, and embeddings for retrieval. - Establish OpenAI-centric RAG: Implement chunking, embeddings, indexing; conduct groundedness checks, prompt test suites, red-teaming, and monitor cost/performance Service Level Objectives (SLOs). - Oversee the fine-tuning lifecycle: Curate datasets, manage training/evaluation, perform bias checks, handle rollback/versioning, and monitor telemetry for tuned models. - Enhance operability: Incorporate observability (OpenAI Observability/OpenTelemetry), token/cost telemetry, retries/backoff, idempotency, and feature flags/canaries; document runbooks and Standard Operating Procedures (SOPs). - Cross-platform & Enterprise Integration: - Design solutions using Azure, AWS, or GCP identity/networking: Leverage Managed Identity, Secret Management, and optional Private Link/private endpoints; enhance security per enterprise controls. - Implement frameworks & vector stores: Utilize OpenAI Agent SDK, LangChain/LangGraph, or Semantic Kernel as needed; integrate Azure Cognitive Search, Redis/pgvector, or managed vector services. - Integrate via Copilot Studio and Microsoft Graph: Connect assistants to Teams, SharePoint, and line-of-business applications where valuable. - Enforce delivery engineering: Implement CI/CD (GitHub Actions/Azure DevOps) and Infrastructure as Code (Terraform/Bicep); support multi-region rollout strategies. ###