Oracle OCI AI Engineer / Enterprise AI Agent Engineer
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- Build OCI-native generative AI applications with strong data grounding and tool contracts
- Build and orchestrate agents with Responses API, MCP, integrations and multi-step workflows
- Operate secure production agents with testing, observability, governance and resilient cloud engineering
Benchmark: Oracle OCI Generative AI + current Senior Platform Software Engineer, AI and enterprise AI-agent platform signals (current Sep 2026). Market refresh: OCI Generative AI Enterprise AI Agents; Responses API; OpenAI-compatible SDKs; File/SQL Search; Code Interpreter; MCP; Oracle AI Database vector/RAG and Select AI; Oracle Integration; IAM/guardrails; testing, observability, containerized deployment and cloud reliability.
Who’s Hiring Right Now
US openings posted in the last 7 days at OpenAI — this role’s own benchmark employers — refreshed daily, as of 2026-11-01. Pulled directly from each company’s public job board; not exhaustive, and postings close fast — worth confirming the details on the employer’s own site before applying.
Build OCI-native generative AI applications with strong data grounding and tool contracts
OCI Generative AI models, APIs + application foundations
Coverage: OCI Generative AI / OpenAI-Compatible APIs / Python SDK / LangChain / Model Selection / Context Engineering
Enterprise grounding with AI Vector Search + Select AI
Coverage: Oracle AI Database / AI Vector Search / RAG / Select AI / NL2SQL / Enterprise Context / Retrieval Quality
Build and orchestrate agents with Responses API, MCP, integrations and multi-step workflows
OCI AI Agent architecture, tools + managed orchestration
Coverage: OCI Responses API / Enterprise AI Agents / Function Calling / File Search / Code Interpreter / Memory / Tool Choice
MCP, Oracle Integration + enterprise action workflows
Coverage: MCP Calling / Oracle Integration / APIs / SQL Tools / External Systems / Human Approval / Multi-Agent Workflows
Operate secure production agents with testing, observability, governance and resilient cloud engineering
Agent evaluation, tracing + responsible enterprise AI
Coverage: Agent Testing / Evals / Tracing / Guardrails / Security / Human-in-the-Loop / Hallucination Controls / Auditability
Production integration, cloud reliability + AI-native engineering
Coverage: OCI IAM / Containers / Kubernetes / Observability / CI-CD / Reliability / Performance / Cost / Agent-Assisted Testing
Role-Readiness Proof / Capstone
Engineer and operate an OCI enterprise AI agent for a real business workflow. Build a typed Python service against OCI Generative AI using the OpenAI-compatible Responses API; ground it with Oracle AI Database vector search, Select AI or another governed enterprise source; add conversation state plus at least two tools using function calling and remote MCP; integrate one operational action through Oracle Integration or an enterprise API; use Code Interpreter, SQL search or file search where justified; enforce OCI IAM, secrets, network and data-access boundaries; create task-success, retrieval, tool-correctness and safety evals with traces; deploy through OCI-managed or containerized runtime with telemetry, SLOs and cost controls; run prompt-injection, tool-failure and rollback drills; then publish architecture, runbook and measured business impact.
Proof Rubric
- Demonstrate sound OCI/model selection
- reliable structured outputs and context management
- high-quality vector/RAG or Select AI grounding
- precise function/MCP contracts
- safe enterprise actions and human approvals
- least-privilege IAM and data controls
- reproducible evals and regression gates
- traceable failures and hallucination analysis
- container/cloud reliability
- latency and cost discipline
- incident/rollback readiness
- measurable task completion and adoption
- and evidence that test or production findings materially improved the system