AIOps Technical Associate

/p

Pay up to  77.50/hr. (No PTO and No Paid Holidays) /p ul li2-4 years in Ops/Technical Operations (MLOps, AIOps, Data Ops, Platform Ops, or similar) liMust have experience with AI/ML Concepts liMust have experience with Cloud Cost Management and Fin Ops li

REQUIRED:

GCP, SQL, reporting tools and basic Python as well as monitoring/observability tools /ul pPlease note that all submissions must include a completed questionnaire for client review.

pSeeking an AI/ML Operations professional for the following role -

verall Responsibilities  pManage operational workflows for model deployments, updates, and versioning across GCP, Azure, and AWS.

pMonitor model performance metrics: latency, throughput, error rates, token usage, and inference quality

pTrack model drift, accuracy degradation, and performance anomalies - escalating to engineering as needed.

pSupport knowledge base operations including vector embedding pipeline health, chunk quality, and refresh cycles in Vertex AI.

pMaintain model inventory and documentation across multi-cloud environments.

pCoordinate model evaluation cycles with Responsible AI and Core Engineering teams

gent & MCP Server Operations  pMonitor AI agent health, performance, and reliability (Auto Gen-based agents, MCP servers)

pTrack agent execution metrics: task completion rates, tool call success/failure, latency, and error patterns

pSupport agent deployment and configuration management workflows

pDocument agent behaviors, known issues, and operational runbooks

pCoordinate with Core Engineering on agent updates, testing, and rollouts

pMonitor MCP server availability, connection health, and integration status

inOps & Cost Management  pTrack and analyze AI/ML cloud spend across GCP (Vertex AI), Azure (OpenAI), and AWS (Bedrock)

pBuild cost dashboards with breakdowns by model, application team, use case, and environment.

pMonitor token consumption, inference costs, and embedding/storage costs.

pIdentify cost optimization opportunities - model selection, caching, batching, rightsizing.

pProvide cost allocation reporting for chargeback/showback to consuming application teams.

pForecast spend trends and flag budget anomalies.

pPartner with Infrastructure and Finance teams on AI cost governance.

pBuild and maintain dashboards for platform performance, model health, agent metrics, and operational KPIs.

pCreate executive and stakeholder reports on platform adoption, usage trends, and cost allocation.

pDevelop Responsible AI dashboards tracking hallucination rates, accuracy metrics, guardrail triggers, and safety incidents.

pMonitor APIGEE gateway traffic patterns and API consumption trends.

pProvide regular reporting to product management on use case performance.

elease Operations Support  pSupport release management processes with pre/post‑deployment validation checks.

pTrack release health metrics for models, agents, and platform components.

pMaintain release documentation, runbooks, and operational playbooks.

pCoordinate with QA, Performance Engineering, and Infrastructure teams during releases.

I Operations  pMonitor guardrail effectiveness and flag anomalies to the Responsible AI team.

pTrack and report on hallucination detection, content safety triggers, and accuracy trends.

pSupport LLM Red Teaming efforts by collecting and organizing evaluation data.

pMaintain audit logs and compliance documentation for AI governance.

ross‑Functional Coordination  pServe as operational point of contact for application teams consuming DxT AI APIs.

pCoordinate with Corporate Security on audit requests and compliance reporting.

pPartner with Infrastructure team on capacity tracking and resource utilization.

pSupport Performance Engineering with load test analysis and results documentation.

asic Qualifications  p2-4 years in an Ops, Analytics, or Technical Operations role (MLOps, AIOps, Data Ops, Platform Ops, or similar)

pUnderstanding of AI/ML concepts: models, inference, embeddings, vector databases, LLMs, tokens, prompts.

pExperience with cloud cost management and Fin Ops - tracking, analyzing, and optimizing cloud spend.

pStrong proficiency with dashboarding and visualization tools…