Site Reliability Engineer

• 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., * 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, 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