SRE/AIOps Manager

Job Description:

Site Reliability Engineering Manager - AI, Analytics & Automation Services

We are seeking an experienced Site Reliability Engineering (SRE) Manager to lead our reliability engineering efforts across our AI, Analytics, and Automation services portfolio. You will spearhead the development of comprehensive observability pipelines, intelligent monitoring systems, and automated resolution frameworks while building and managing a high-performing team of SREs. This role is critical to ensuring the reliability, scalability, and performance of our AI solutions, Databricks analytics platform, and UiPath automation infrastructure.

Key Responsibilities

Observability & Monitoring Excellence

• Design and implement end-to-end observability pipelines spanning AI solutions, data processing workflows, and automation execution environments
• Establish comprehensive monitoring strategies for AI model performance, drift detection, data quality, and service health across Databricks and UiPath platforms
• Build real-time dashboards and alerting systems that provide actionable insights into system performance, resource utilization, and service reliability
• Develop custom metrics and KPIs specific to AI/ML workloads, including model accuracy, latency, throughput, and resource consumption
• Implement distributed tracing and logging solutions to enable rapid troubleshooting across complex AI and automation pipelines

Automated Resolution & Self-Healing Systems

• Architect and deploy automated incident response systems that can detect, diagnose, and resolve common reliability issues without human intervention
• Build intelligent event-triggered runbook automation
• Implement chaos engineering practices to proactively identify and strengthen system weaknesses
• Develop automated remediation workflows for infrastructure issues, service degradations, and capacity constraints
• Create self-healing mechanisms for AI inference services, data pipeline failures, and automation workflow interruptions

Team Leadership & Development

• Build, mentor, and lead a team of Site Reliability Engineers with expertise in AI/ML operations, data platforms, and automation technologies
• Establish SRE best practices, standards, and processes tailored to AI and automation workloads
• Foster a culture of reliability engineering, continuous improvement, and data-driven decision making
• Conduct regular performance reviews, career development discussions, and technical skill assessments
• Collaborate with engineering teams to embed reliability principles into the software development lifecycle

Platform Reliability & Performance

• Ensure near zero downtime and optimal performance of AI solutions, Databricks analytics workloads, and UiPath automation processes
• Design and implement disaster recovery and business continuity plans for critical AI and automation services
• Optimize resource allocation and cost management across cloud infrastructure supporting AI, analytics, and automation workloads
• Establish and maintain service level objectives (SLOs) and error budgets for all managed services
• Drive capacity planning initiatives to support growing AI model deployment and automation scale requirements

Cross-Functional Collaboration

• Partner with AI/ML developers to integrate reliability considerations into AI solutions and deployment pipelines
• Work closely with data engineering teams to ensure robust, monitored data flows within Databricks environments
• Collaborate with automation developers to build resilient UiPath bot deployment and execution frameworks
• Interface with security teams to implement observability solutions that maintain compliance and data protection standards

Required Qualifications

• 7+ years of experience in Site Reliability Engineering, DevOps, or similar infrastructure roles
• 2+ years of management experience leading technical teams
• Hands-on experience with observability tools such as Prometheus, Grafana, ELK Stack, Datadog, or New Relic
• Proficiency in Infrastructure as Code (Terraform, CloudFormation, Ansible)
• Strong scripting and automation skills (Python, Go, Bash, PowerShell)
• Familiarity with Databricks platform administration, cluster management, and workflow orchestration
• Knowledge of UiPath platform architecture, orchestrator management, and bot deployment strategies
• Understanding of data pipeline monitoring, data quality validation, and ETL/ELT process reliability
• Experience with ML model monitoring, A/B testing infrastructure, and feature store management
• Proven track record of building and scaling high-performing engineering teams
• Strong analytical and problem-solving skills with ability to troubleshoot complex distributed systems
• Excellent communication skills with ability to present technical concepts to executive stakeholders
• Experience driving cross-functional initiatives and influencing without direct authority
• Demonstrated ability to balance operational excellence with strategic innovation

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