Staff AI-Ops Engineer
Sumitomo Mitsui Banking Corporation2 hours ago
Charlotte, NC, USAStaff+
Responsibilities
- Design and operate the MLOps/LLMOps backbone for AI models, prompts, pipelines, and agents on Databricks and Azure.
- Build CI/CD pipelines, infrastructure-as-code, and deployment strategies including canary, blue/green, shadow, and automated rollback releases.
- Implement lineage, version control, auditability, and quality gates across data, prompts, retrievals, models, and responses.
- Build observability for data quality, model and data drift, retrieval and hallucination health, application performance, business KPIs, and cost.
- Establish automated regression, A/B, canary, shadow, champion-challenger, and human-in-the-loop evaluation processes.
- Operationalize responsible-AI, security, privacy, authentication, authorization, and secret-management controls.
- Support day-two operations through model cards, API and SLA contracts, runbooks, incident response, and escalation readiness.
- Evaluate emerging AI-Ops tooling, improve platform reliability and efficiency, and mentor engineering teams on MLOps/LLMOps practices.
Requirements
- Bachelor’s degree in Computer Science, Machine Learning, Data Science, or a related field.
- 5+ years of hands-on experience deploying, operating, and maintaining GenAI or advanced ML models in production, focused on MLOps/LLMOps.
- 3+ years of experience with Python and GenAI frameworks or tools such as Databricks Vector Search, Azure AI Search, Azure AI Document Intelligence, LangGraph, Haystack, and LlamaIndex.
- Deep hands-on expertise with MLflow, Databricks, Databricks Asset Bundles, and Azure.
- Experience developing and deploying RESTful services, containerized systems, and automated CI/CD systems.
- Experience building observability, monitoring, and alerting for AI data and model drift, evaluation metrics, hallucination or grounding health, performance, and cost.
- Working knowledge of prompt engineering, embedding models, RAG evaluation, and vector databases.
- Working knowledge of PyTorch, TensorFlow, and Hugging Face Transformers.
- Familiarity with AI governance, responsible AI, and security and privacy controls in regulated environments.
- Excellent communication and collaboration skills with the ability to influence technical and non-technical stakeholders.
Benefits
- Hybrid work model combining work from home and an SMBC office, with employees required to live within a reasonable commuting distance of their office.
- Specific hybrid schedule details are provided during the interview process.
- Reasonable accommodations are available during candidacy for applicants with disabilities.