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# Lead Software Engineer, Platform

- **Company:** Recruiting from Scratch
- **Location:** San Francisco, CA, United States (Remote available)
- **Experience:** Expert
- **Salary:** $220,000.0 - $320,000.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Amazon Web Services, Cloud Computing, DevOps, Distributed Systems, Fault Tolerance, Python (Programming Language), Machine Learning, Software Deployment, Software Engineering, Data Processing, Cloud Platform System, Delivery Pipeline, Concurrency, Caching, Core Api, Backend, Build Management, Information Technology, Low Latency, Machine Learning Operations
- **Published:** October 27, 2026
- **Apply:** https://www.careerbuilder.com/job-details/lead-software-engineer-platform-san-francisco-ca--3b5926a8-f695-41cc-85e8-0ccbe27c94eb

## About the Role

Software Engineering, Software Engineering, Startup, Benchmarking, Funding, Revenue Growth, Artificial Intelligence (AI), Cloud Computing, Technical Strategy, Distributed Computing, * 5+ years of software engineering experience

 * Experience building platform infrastructure or distributed backend systems
 * Experience working at high-growth startups or high-performing technology companies
 * Experience owning production infrastructure serving customer-facing applications
 * Experience designing highly scalable distributed production systems
 * Experience building mature infrastructure supporting rapidly growing businesses
 * Experience operating production systems with significant uptime and reliability requirements
 * Strong startup ownership with demonstrated technical leadership
 * Experience mentoring engineers or leading technical initiatives preferred, * Strong backend engineering experience with Python (Go or Rust experience also valued)
 * Experience building distributed systems handling high-throughput workloads
 * Experience designing cloud-native infrastructure and production deployments
 * Strong understanding of distributed task orchestration and workload scheduling
 * Experience optimizing production infrastructure for reliability, latency, and cost efficiency
 * Strong cloud infrastructure expertise across AWS, GCP, or equivalent platforms
 * Experience working closely with machine learning infrastructure and model serving
 * Experience designing scalable backend services and platform APIs
 * Strong software engineering fundamentals across scalability, reliability, concurrency, and distributed architecture
 * Full-stack engineering capability with strong application engineering fundamentals (not purely DevOps), * Bachelor's degree in Computer Science or another technical discipline from a top engineering program preferred
 * Strong academic background from a Top Computer Science university preferred
 * Exceptional candidates with outstanding platform engineering experience considered

Soft Skills

 * Strong systems thinking
 * High ownership mentality
 * Excellent technical communication
 * Comfortable operating with ambiguity
 * Strong collaboration skills
 * Startup mentality with high execution velocity
 * Structured problem solver
 * Engineering leadership mindset
 * Passion for building highly reliable infrastructure
 * Comfortable owning production systems end-to-end

## Description

* Design and build highly scalable distributed systems supporting millions of production document processing jobs
 * Architect platform infrastructure emphasizing reliability, latency, scalability, and operational efficiency
 * Improve cloud infrastructure, deployment pipelines, orchestration systems, and workload scheduling
 * Optimize model serving infrastructure alongside ML engineering teams
 * Build backend platform services using Python while supporting distributed production systems
 * Design scalable task orchestration, messaging, caching, and data processing infrastructure
 * Improve platform observability, monitoring, fault tolerance, and operational excellence
 * Lead architecture decisions around distributed systems, cloud infrastructure, and platform scalability
 * Build internal platform tooling that accelerates engineering productivity
 * Drive platform performance, infrastructure cost optimization, and production reliability
 * Participate in platform ownership and on-call rotations while continuously improving system health
 * Collaborate closely with ML, Product Engineering, Infrastructure, and Leadership to enable rapid product development
 * Mentor engineers and establish engineering best practices across platform architecture