Ivy Partners
Consulting
SeniorMLOps/LLMOpsEngineer
Neural analysis suggests this role is
optimal for senior-manager candidates.
“Senior MLOps/LLMOps Engineer at Ivy Partners. Skills: MLOps, LLMOps, Data Platform Engineering, Production Python. Design ingestion pipelines. Implement ingestion pipelines”
Industry & Context.
Root cause analysis; Troubleshooting
What They're Looking For.
Must Have
Extensive hands-on experience ML Ops, Proven experience LLM systems, Background observability systems, Background tracing systems, Background evaluation systems, Excellent command production-grade Python, Knowledgeable governance, Knowledgeable PII handling, Knowledgeable regulated environments, Experience Azure, Experience AWS, Familiar vector databases, Familiar eval pipelines, Familiar failure analysis, Pragmatic mindset, Technical ownership end-to-end, Capable operating critical systems, Experience multi-tenant SaaS, Knowledge SQL, Knowledge TypeScript, Interest modern AI tooling
What You'll Do.
Design ingestion pipelines
Implement ingestion pipelines
Construct PII redaction mechanisms
Construct safety classification mechanisms
Construct abuse classification mechanisms
Set storage architecture
Set retention policies
Implement query layers
Develop eval mining workflows
Develop regression detection workflows
Integrate LLM-as-judge pipelines
Build automatic triage mechanisms
Ensure platform reliability
Ensure platform observability
Ensure platform access control
Support scalable onboarding
Full Job Description
Our Mission Ivy Partners is a Swiss consulting firm that helps companies navigate strategic, technological, and organizational challenges. We are committed to providing our employees with a career that supports both their personal and professional growth. We guide them in skill development and offer genuine opportunities for advancement. As a Senior ML Ops / LLM Ops Engineer at Ivy Partners, you will be responsible for: \- Designing and implementing ingestion pipelines for ML/LLM traffic in production \- Constructing mechanisms for PII redaction and classifying safety/abuse \- Setting architecture of storage, retention policies, and data governance \- Implementing dashboards and query layers for operational debugging \- Developing workflows for eval mining and regression detection \- Integrating autoraters and LLM-as-judge pipelines \- Building automatic triage mechanisms for failure detection \- Ensuring the reliability, observability, and access control of the platform \- Supporting scalable onboarding of multiple tenants \- Making decisions on tooling and hosting (self-hosted vs managed SaaS) About You You are our ideal candidate if you: \- Have extensive hands-on experience in ML Ops / Data Platform Engineering \- Have proven experience with LLM systems in production \- Possess a strong background in observability, tracing, and evaluation systems \- Have excellent command of production-grade Python \- Are knowledgeable in governance, PII handling, and regulated environments \- Have experience with Azure and/or AWS \- Are familiar with vector databases, eval pipelines, and failure analysis \- Exhibit a pragmatic mindset and technical ownership from end-to-end \- Are capable of operating critical systems with a focus on reliability \- Have experience in multi-tenant SaaS environments \- Have knowledge of SQL and TypeScript for dashboards \- Have interest in modern AI tooling (Claude, OpenAI, GitHub, etc.). Why Join Ivy Partners? Care | We care about our employees
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