Sr. Manager, SRE & Performance

Omnissa•Mountain View, CA

1d•$223,000 - $310,000•Hybrid

About The Position

We are looking for a Senior Manager of Site Reliability Engineering (SRE) & Performance Engineering to lead teams responsible for the reliability, scalability, performance, and operational excellence of our distributed SaaS platform. This is a hands-on technical leadership role for someone who can operate at the intersection of software engineering, distributed systems, cloud infrastructure, SRE, and performance engineering. You will lead engineers while partnering closely with development, architecture, security, SaaS operations, and product teams to ensure our services are designed and operated for scale, resilience, efficiency, and predictable performance. You will help establish engineering standards around SLOs, observability, performance testing, capacity planning, incident management, production readiness, and continuous reliability improvement.

Requirements

12+ years of software engineering experience, with significant experience building and operating large-scale backend or distributed systems.
5+ years of engineering leadership/management experience, preferably leading SRE, Performance Engineering, Platform Engineering, Infrastructure, or backend engineering teams.
Proven ability to build, mentor, and develop high-performing engineering teams, including senior and staff-level engineers.
Strong ability to balance people leadership, technical strategy, operational priorities, and business objectives.
Experience influencing engineering practices across teams without relying solely on organizational authority.
Demonstrated ability to work effectively with senior engineers, architects, engineering managers, product leaders, security teams, and executive stakeholders.
Strong understanding of distributed systems and microservices architectures, including scalability, availability, consistency, fault tolerance, failure modes, and architectural trade-offs.
Strong software engineering background, preferably with experience in C#/.NET, Go or Java, and the ability to participate meaningfully in architecture, design, and code-level technical discussions.
Deep understanding of Linux systems, including processes, memory, CPU scheduling, networking, file systems, containers, and system-level performance diagnostics.
Strong experience with Docker and container orchestration using HashiStack technologies such as Nomad, Consul, and Vault.
Experience operating high-scale data platforms using technologies such as Kafka, PostgreSQL, OpenSearch, Redis/Valkey, or equivalent technologies.
Strong cloud experience, preferably with AWS, including services such as EC2, EKS, MSK, Aurora/RDS, OpenSearch, networking, storage, and cloud observability services.
Strong understanding of CI/CD, Infrastructure as Code, deployment automation, release strategies, and modern DevOps practices.
Deep understanding of SRE principles, including SLIs/SLOs, error budgets, availability engineering, incident management, production readiness, operational toil, and reliability automation.
Proven experience designing and implementing observability strategies using metrics, logging, tracing, dashboards, and actionable alerting.
Strong understanding of performance engineering methodologies, including workload modeling, benchmarking, profiling, stress/load testing, scalability analysis, and performance regression detection.
Experience diagnosing performance issues across applications, databases, operating systems, containers, infrastructure, and network layers.
Experience with capacity planning and forecasting, including translating workload growth into infrastructure and service capacity requirements.
Strong understanding of resilience engineering, including graceful degradation, retries, timeouts, circuit breakers, backpressure, rate limiting, disaster recovery, and failure testing.
Demonstrated ability to turn production incidents and performance findings into systemic engineering improvements rather than tactical fixes.

Responsibilities

Lead and grow SRE and Performance Engineering teams, providing technical direction, coaching, career development, and establishing a strong culture of ownership and engineering excellence.
Define and drive the organization's SRE and performance engineering strategy, including reliability goals, performance objectives, scalability standards, and operational readiness requirements.
Partner with engineering teams to ensure systems are designed for high availability, scalability, fault tolerance, performance, and operability from the beginning rather than addressing these concerns after deployment.
Establish and drive adoption of SLIs, SLOs, error budgets, service health indicators, and production readiness criteria for critical services.
Lead performance engineering initiatives across distributed systems, including workload modeling, benchmarking, profiling, scalability testing, capacity planning, and bottleneck analysis across CPU, memory, I/O, storage, database, and network layers.
Drive observability strategy across metrics, logs, traces, dashboards, and alerting, while improving signal quality and reducing noisy or non-actionable alerts.
Provide technical leadership during complex production incidents, helping teams diagnose distributed system failures, latency spikes, resource contention, database issues, network problems, and cascading failures.
Drive effective incident management, RCA/postmortem practices, corrective actions, and systemic reliability improvements, ensuring lessons from incidents translate into engineering changes.
Partner with architects and senior engineers on system design and architecture reviews, challenging designs around scalability, resilience, failure modes, performance, data architecture, and operational complexity.
Establish scalable approaches for performance regression detection and reliability validation within CI/CD pipelines, enabling issues to be identified earlier in the development lifecycle.
Drive capacity management and forecasting, using production telemetry, workload characteristics, and performance models to anticipate infrastructure requirements and scalability limits.
Improve platform efficiency through performance optimization, infrastructure right-sizing, and cost-aware engineering, balancing reliability, performance, and cloud cost.
Champion automation and engineering-driven operations, reducing manual operational work and toil through software, tooling, Infrastructure as Code, and automated remediation.
Establish measurable SRE and performance KPIs, such as availability/SLO attainment, MTTR, change failure rate, alert quality, performance regression rates, capacity headroom, operational toil, and recurring incident reduction.
Collaborate across Product, Engineering, Security, Cloud/SaaS Operations, and Architecture organizations to deliver secure, resilient, scalable, and production-ready services.