Senior AI Engineer
oraclecloud
Job Description
- Own end-to-end deployment of AI applications on Azure — from classical ML models and Azure OpenAI Service integrations through to production release, monitoring, and iteration.
- Build and evaluate core ML models where GenAI isn't the right tool — classification, regression, forecasting, clustering, or recommendation problems using traditional ML techniques.
- Design and implement guardrails — content filtering, prompt injection defence, PII redaction, output validation, and human-in-the-loop checkpoints for high-risk actions.
- Build and maintain MLOps/LLMOps pipelines — CI/CD for models and prompts, feature engineering and data pipelines, automated evaluation harnesses, versioning for models/prompts/embeddings/fine-tunes, and rollback mechanisms.
- Manage the model lifecycle — model selection and routing (classical ML vs. smaller LLMs vs. frontier models by task complexity and cost), performance benchmarking, cost-per-call/cost-per-inference tracking, and deprecation/upgrade planning.
- Implement observability — logging, tracing, and alerting for LLM applications (token usage, latency, hallucination/error rates, user feedback loops).
- Architect RAG and agentic systems — vector store design, retrieval tuning, orchestration frameworks (LangGraph, Semantic Kernel, or equivalent), and multi-agent workflows where applicable.
- Collaborate cross-functionally with product owners, architects, and business stakeholders to translate requirements into scoped, deployable AI features.
- Contribute to AI governance — support responsible AI reviews, model risk assessments, and documentation required for enterprise sign-off.