Site Reliability Engineer Sylmar - CA - California

Job Summary

We are seeking an experienced engineer who can analyze, diagnose, and optimize performance and reliability of large-scale distributed systems. This role requires deep technical understanding across the entire application stack, the ability to read and reason about code, and the capability to provide data-backed answers to both engineering teams and business stakeholders.

This role goes beyond traditional operations or DevOps. The successful candidate will think like a software engineer, act like a systems engineer, and operate with a production-first mindset.

Key Responsibilities

Performance & Reliability Engineering

Analyze and resolve performance issues such as high latency, slow login, throughput degradation, and system instability.

Perform deep, end-to-end investigations across the full stack including:

Load balancers and traffic routing

Web server and application runtime configurations

Middleware and messaging systems

Database performance (queries, indexing, pooling)

Kubernetes clusters (pods, resources, scaling behavior)

Linux OS tuning (CPU, memory, IO, ulimits, networking)

Identify root causes and propose clear, actionable engineering solutions.

Distributed Systems Design

Design, review, and influence high-performance, highly-available distributed architectures.

Evaluate trade-offs related to scalability, latency, fault tolerance, and cost.

Partner with development teams early to prevent reliability and performance issues before production.

Capacity Planning & Scalability

Assess system readiness for growth scenarios such as:

We plan to onboard 10,000 users in 6 months - can the system support it?

Perform capacity and scale analysis for:

Application tiers

Databases

Messaging systems

Kubernetes compute and storage

Provide evidence-based recommendations supported by metrics, benchmarks, and production data.

Engineering Collaboration

Work closely with software engineering teams to:

Review performance-critical code paths

Propose improvements at code, configuration, or infrastructure level

Improve system observability (metrics, logs, traces)

Communicate complex technical findings clearly to both engineers and business stakeholders.

Required Technical Skills

Strong understanding of distributed systems and performance engineering

Ability to read, analyze, and troubleshoot Java code

Hands-on experience with:

Kubernetes (resource management, scaling, container behavior)

Linux internals and tuning

PostgreSQL (queries, indexing, performance optimization)

Proven experience building or operating high-availability, high-throughput systems

Strong analytical and problem-solving skills with a data-driven approach

Nice to Have

Experience with Azure cloud services

Messaging systems such as ActiveMQ

Load testing and benchmarking experience

Background in roles such as SRE, Performance Engineering, Platform Engineering

Required Skills & Qualifications

Technical Skills

Hands-on experience with cloud platforms (Azure.

Strong scripting skills (e.g., Python, Bash, PowerShell, or similar).

Experience with deployment pipelines, automation, and monitoring tools.

Solid understanding of cloud infrastructure, networking, and application operations.

LLM & AI Experience

Practical experience working with Large Language Models (LLMs).

Familiarity with applying LLMs to engineering or operational workflows is required.

Professional Attributes

Strong desire to learn and deeply understand complex systems.

Self-starter with the ability to take ownership and drive initiatives independently.

Demonstrates leadership, accountability, and problem-solving mindset.

Strong collaboration and communication skills.