Senior Software Engineer, Platform

Location: San Francisco, CA (Onsite – 5 Days/Week)
Company Stage of Funding: Series A/B AI Infrastructure + Document Intelligence Platform
Office Type: In-Person (San Francisco)
Salary: $220,000 – $300,000 Base
Equity: Competitive Equity Package
Bonus: Competitive Total Compensation
Visa: Sponsorship Available (Transfers Supported)

Our client is building the infrastructure layer that enables AI systems to understand complex enterprise documents at scale.

The platform transforms PDFs, spreadsheets, images, financial documents, healthcare records, legal files, and other unstructured data into highly accurate structured outputs that power AI applications and LLM workflows.

Backed by leading venture investors with over $100M in funding, the company has experienced explosive growth and is now processing tens of millions of document pages every month for customers ranging from startups to Fortune 10 enterprises.

The platform powers:

• Document Intelligence Infrastructure
• AI Data Ingestion Pipelines
• LLM Data Processing Systems
• OCR & Document Understanding
• Enterprise Knowledge Extraction
• Workflow Automation Infrastructure
• Structured Data Generation
• Model Serving Platforms
• AI Processing Pipelines
• Distributed Compute Systems

Engineering challenges include:

• Building highly reliable distributed systems
• Scaling document processing infrastructure
• Optimizing model serving performance
• Designing fault-tolerant platform services
• Managing large-scale cloud infrastructure
• Task orchestration and workload scheduling
• High-throughput processing pipelines
• Platform reliability and observability
• Cost optimization at scale
• AI infrastructure and production ML systems

The company operates at the intersection of AI infrastructure, distributed systems, and enterprise software while maintaining the speed, ownership, and impact of an early-stage startup.

The culture values:

• Exceptional engineering talent
• Ownership and accountability
• Technical excellence
• Product craftsmanship
• Learning velocity
• High trust
• Fast execution
• Customer obsession
• Pragmatic decision making
• Long-term thinking

What You Will Do

• Own and improve the core platform powering document processing workloads
• Design and scale distributed systems handling millions of documents
• Improve platform reliability, latency, throughput, and cost efficiency
• Build infrastructure supporting production AI and ML workloads
• Design workload scheduling and task orchestration systems
• Optimize model serving infrastructure and inference pipelines
• Collaborate closely with ML engineers to deploy and scale AI systems
• Design and improve backend services, APIs, and platform tooling
• Build cloud-native infrastructure and deployment systems
• Own databases, queues, processing pipelines, and service reliability
• Develop observability, monitoring, alerting, and operational tooling
• Drive architecture decisions across critical platform initiatives
• Participate in on-call rotations and incident response
• Lead reliability and performance improvement efforts
• Mentor engineers through design reviews and technical leadership
• Help define engineering standards and platform best practices
• Operate as a senior technical leader within a small, high-impact team
• Build infrastructure that directly powers customer-facing AI products

Ideal Candidate Background

• 5–15 years of software engineering experience
• Strong platform, backend, or infrastructure engineering experience
• Experience operating large-scale distributed systems
• Experience scaling production infrastructure
• Strong software engineering fundamentals
• Experience with cloud-native architectures
• Strong backend development experience
• Experience building reliable production systems
• Experience supporting high-availability platforms
• Strong system design and architecture skills
• Experience collaborating with ML or AI teams
• Python proficiency preferred
• Experience with Go or Rust also valuable
• Experience with workload orchestration systems
• Experience with platform observability and monitoring
• Experience with production cloud environments
• Comfortable participating in on-call rotations
• Ability to thrive in fast-moving startup environments
• Strong communication and collaboration skills

Strong Signals

Platform & Infrastructure Signals

• Staff or Principal Engineer experience
• Owned critical platform infrastructure
• Built distributed systems at scale
• Designed highly available backend platforms
• Experience with service reliability engineering
• Experience operating cloud infrastructure
• Platform engineering leadership experience
• Performance optimization expertise
• Experience managing large-scale workloads
• Infrastructure architecture ownership

Startup Signals

• Early-stage startup experience (Seed–Series B)
• High-growth startup experience
• Small-team ownership experience
• Built systems from scratch
• Operated in highly ambiguous environments
• Strong bias toward execution
• Demonstrated technical leadership
• Fast promotion trajectory
• Founder or founding engineer experience
• Startup builder mentality

Engineering Signals

• Distributed systems expertise
• Cloud infrastructure experience
• AI infrastructure exposure
• Model serving optimization experience
• Platform reliability ownership
• Observability and monitoring expertise
• Database scaling experience
• Event-driven architecture experience
• Strong application-level engineering skills
• Proven history of shipping production systems

Compensation & Benefits

• Base Salary: $220,000 – $300,000+
• Competitive Equity Package
• Visa Sponsorship Available
• Opportunity to join one of the fastest-growing AI infrastructure companies
• Significant ownership over core platform architecture
• Direct impact on systems processing millions of documents monthly
• Work alongside elite infrastructure and AI engineers
• Small team with outsized influence
• Strong product-market fit and hypergrowth trajectory
• High autonomy and technical ownership
• Exposure to cutting-edge AI infrastructure challenges
• Opportunity to shape foundational AI platform technology

Why Join

This is an opportunity to build the infrastructure layer powering the next generation of AI applications.

Rather than working on isolated backend services, you'll own systems responsible for transforming massive volumes of complex enterprise data into AI-ready information used by hundreds of customers every day.

You'll work on:

• Distributed systems
• AI infrastructure
• Model serving platforms
• Large-scale cloud architecture
• Reliability engineering
• Document processing systems
• Workflow orchestration
• Enterprise AI infrastructure
• Performance optimization
• Production-scale platform engineering

The role offers a rare combination of startup ownership, infrastructure scale, AI exposure, and technical depth.

If you enjoy solving hard distributed systems problems, building reliable platforms, optimizing infrastructure at scale, and operating with significant ownership, this role offers exceptional scope and career upside.