AI Database Platform Lead

Bisoftllc is looking for AI-First Data Platforms Lead –

Key Responsibilities

•                Own the enterprise database platform strategy, architecture, governance, and technology roadmap.

•                Lead the transformation from traditional DBA operations to an AI-first Database Platform Engineering model.

•                Drive AI-powered automation for database provisioning, monitoring, maintenance, performance tuning, and incident management.

•                Build and manage self-service database provisioning capabilities to accelerate engineering delivery and reduce manual effort.

•                Ensure database platforms are secure, scalable, resilient, highly available, and cost-efficient across on-premises and cloud environments.

•                Lead database modernization, consolidation, migration, and cloud adoption initiatives.

•                Establish standards, best practices, governance, and lifecycle management for enterprise database platforms.

•                Implement observability, predictive monitoring, and AIOps capabilities to proactively prevent outages and improve reliability.

•                Partner with Engineering, Infrastructure, Security, Architecture, and Application teams to deliver platform services and approved patterns.

•                Drive adoption of Infrastructure-as-Code (IaC), DevOps, CI/CD, and Database-as-a-Service (DBaaS) capabilities.

•                Ensure compliance, data protection, access controls, backup, recovery, and disaster recovery readiness.

•                Mentor and develop database engineers while fostering a culture of automation, innovation, and operational excellence.

•                Evaluate emerging database, AI, and cloud technologies to continuously improve platform capabilities.

•                Optimize platform costs through standardization, automation, capacity planning, and resource utilization.

Business Impact

•                Reduces operational risk through intelligent automation and standardized platforms.

•                Improves performance, availability, reliability, and security of enterprise databases.

•                Accelerates provisioning from days to minutes through self-service capabilities.

•                Enhances compliance and governance while reducing manual administrative effort.

•                Lowers long-term support and infrastructure costs through automation and platform rationalization.

•                Enables engineering teams to move faster with AI-enabled platform services and expert guidance.

•                Creates a scalable foundation that supports enterprise growth, cloud strategy, and future AI initiatives.

Key Success Measures

•                Significant reduction in manual DBA effort through AI and automation.

•                Faster database provisioning and deployment cycles.

•                Improved uptime, reliability, and recovery capabilities.

•                Reduced incident volume and Mean Time to Resolution (MTTR).

•                Increased adoption of self-service database services.

•                Lower total cost of ownership (TCO) through optimization and standardization.