Senior Software Engineer (Distributed Systems)

TL;DR

Senior Software Engineer (Distributed Systems): Designing and optimizing high-performance core software platforms and microservices with an accent on scalability, low-latency, and resource efficiency. Focus on eliminating architectural bottlenecks, optimizing the data layer, and ensuring seamless integration with AWS cloud infrastructure.

Location: Hybrid (USA, Pleasanton, CA). Must spend at least 50% of time each quarter in the office or in the field.

Salary: $160,100 – $285,100 USD

Company

A Fortune 500 company providing a leading AI platform for managing human capital and financial management.

What you will do

• Lead the technical design of decoupled, horizontally scalable microservices optimized for high throughput and low latency.
• Write production-ready code for critical paths and refactor legacy components to maximize efficiency.
• Conduct deep-dive profiling and memory analysis using APM tools to resolve performance bottlenecks proactively.
• Optimize the data layer through caching strategies, database schema refinement, and efficient serialization formats.
• Partner with Cloud Infrastructure teams to align software design with AWS architecture for maximum compute and network efficiency.
• Drive rigorous code reviews and mentor other engineers on writing performance-first code.

Requirements

• Bachelor’s or Master’s degree in Computer Science, Engineering, or equivalent practical work experience.
• 8+ years of professional software development experience in Python, GoLang, or Java/C++.
• 4+ years of experience designing, building, and evolving scalable distributed microservices architectures.
• Proven track record of diagnosing complex performance issues, including memory leaks and CPU bottlenecks.
• Must be based in the USA to meet hybrid office requirements.

Nice to have

• Experience with profiling and APM tools such as Datadog, New Relic, OpenTelemetry, or CloudWatch.
• Expertise in database optimization and multi-tier caching layers (e.g., Redis, Memcached).
• Deep understanding of AWS or GCP compute, memory, and networking boundaries.
• Experience establishing micro-benchmarking and load testing using tools like Locust, JMeter, or k6.
• Strong knowledge of asynchronous programming, multi-threading, and distributed systems concepts.

Culture & Benefits

• Flex Work policy allowing for a balance of remote work and intentional in-person collaboration.
• Collaborative environment rooted in integrity, empathy, and shared enthusiasm.
• Competitive compensation including a base salary, bonus plan, and annual refresh stock grants.
• Access to tools and support for long-term professional development and career growth.