Lead Software Engineer, Platform
About The Position
The company is building the infrastructure layer that transforms complex, unstructured documents into production-ready structured data for modern AI applications. Its platform powers document understanding across PDFs, spreadsheets, images, scanned documents, and enterprise records, enabling organizations to build reliable AI workflows on top of previously inaccessible data. Today, hundreds of companies—from high-growth startups to Fortune 10 enterprises—depend on the platform to process tens of millions of documents while maintaining exceptional accuracy, reliability, and performance. Backed by Andreessen Horowitz, Benchmark, and First Round Capital with over $100M in funding, the company has experienced more than 8x year-over-year revenue growth and continues to establish itself as one of the fastest-growing AI infrastructure companies in the market. As a Lead Software Engineer, Platform, you'll own the core infrastructure responsible for document processing, distributed orchestration, platform reliability, model serving, and cloud infrastructure while partnering closely with ML engineers and product teams to scale one of the industry's most advanced AI document processing platforms. This is a rare opportunity to join an AI-native infrastructure company where engineers own foundational platform architecture, influence long-term technical strategy, and build systems processing millions of documents for mission-critical enterprise AI workloads.
Requirements
- 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
- 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)
Nice To Haves
- Experience mentoring engineers or leading technical initiatives preferred
- 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
Responsibilities
- Own and evolve the core platform powering large-scale document processing workloads
- 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
Benefits
- Competitive Equity Package
- Visa Sponsorship Available
- Opportunity to build foundational infrastructure powering enterprise AI applications
- Direct collaboration with Engineering Leadership and Founders
- Significant ownership over platform architecture and technical direction
- High-impact engineering culture with exceptional career growth
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What This Job Offers
Job Type
Full-time
Career Level
Senior
