SRE

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, I/O, 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.

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 For applications and inquiries, contact:hirings@openkyber.com