Data & AI ProductOps Lead

About the role

This senior technical leadership position is responsible for establishing and scaling a Data & AI ProductOps practice. The role combines hands‑on expertise in modern data, AI platforms and DevOps with strong governance, observability and service‑management integration.

Key responsibilities

• Define and lead the Data & AI ProductOps practice, creating operating models, standards, reusable patterns and governance across DataOps, MLOps, LLMOps and AgentOps.
• Design and implement operational readiness, support models (L0‑L3), SLO frameworks, monitoring, incident management and change/release processes for data, BI, ML, GenAI and AI‑agent products.
• Assess client maturity, design target operating models and deliver ProductOps capabilities within client environments, overseeing architecture and implementation.
• Lead multidisciplinary teams, provide technical oversight, and engage senior stakeholders across product, engineering, platform, governance and service‑management functions.

Required profile

• Bachelor’s degree in Computer Science, Engineering, Data/AI, Information Systems or related field.
• 10+ years of experience in Data Engineering, AI/ML, DataOps, DevOps, SRE or Product Operations.
• Proven experience establishing production operating capabilities for Data and AI products, preferably with government agencies or large enterprises in the GCC.

Required skills

• Databricks, Informatica IDMC, Microsoft Fabric, Power BI, Azure Data Services, Spark, Delta Lake
• Kafka, APIs, CDC, batch and streaming integration
• MLflow, Azure AI/ML, model serving, RAG, vector search, AI evaluation, AI observability
• LangChain, LangGraph, Semantic Kernel
• Azure DevOps, GitHub, CI/CD, Docker, Kubernetes, Terraform, Python, SQL
• OpenTelemetry, Azure Monitor, Application Insights
• ServiceNow (ITSM)