Senior / Staff Backend Engineer – AI Agents Platform

Location - Redwood City, CA (Hybrid – 3 Days per Week)

Exceptional Candidates from Major US Tech Hubs May Be Considered

Compensation - $200,000 – $250,000 Base + Bonus + Competitive Equity (OTE: $220,000 – $300,000+)

Visa - Visa Sponsorship Available on a Case-by-Case Basis

Company Stage - High-Growth AI Company

Industry - AI Agents, Enterprise AI, Vertical SaaS, Backend Infrastructure, Distributed Systems

About the Company

The company is building autonomous AI agents that function like experienced operators, enabling businesses to automate complex operational workflows with human-level reasoning and decision-making.

Its AI platform combines large language models, distributed backend systems, production-grade infrastructure, and multi-step autonomous agent workflows to execute sophisticated business processes at enterprise scale. Already deployed across millions of customer endpoints, the platform is rapidly becoming one of the fastest-growing AI products in its market.

Backed by leading investors and experiencing exceptional commercial traction, the engineering organization is expanding rapidly to build the next generation of AI-native backend infrastructure powering reliable, production-scale autonomous agents.

As a Senior / Staff Backend Engineer, you'll architect the core platform powering AI agents, distributed backend services, APIs, and production infrastructure while working alongside a high-performing engineering team solving challenging systems problems at scale.

This is a rare opportunity to join a rapidly growing AI company where you'll own foundational platform architecture, influence engineering direction, and build production AI systems deployed across real enterprise customers.

What You'll Do

• Architect and build the backend platform powering autonomous AI agents
• Design scalable distributed systems supporting production AI workloads
• Build reliable APIs, backend services, and platform infrastructure from the ground up
• Design and implement multi-step autonomous AI agent systems
• Improve system reliability, scalability, observability, latency, and production performance
• Design clean service contracts, APIs, and platform abstractions across internal and external systems
• Build production infrastructure supporting AI reasoning, orchestration, and execution workflows
• Own architecture decisions across backend services, infrastructure, and platform engineering
• Partner closely with engineering leadership to shape long-term platform architecture
• Own high-impact engineering initiatives from technical design through production deployment
• Help establish engineering standards, backend best practices, and platform quality
• Operate with high autonomy while solving complex distributed systems challenges

Ideal Candidate Background

Experience Requirements

• 6+ years of experience in backend software engineering
• Experience building and scaling production AI/ML platforms or products
• Experience designing and operating distributed backend systems at meaningful production scale
• Experience working in fast-paced, high-growth startup environments
• Experience leading technical architecture for high-impact engineering initiatives
• Experience owning backend systems from design through production operations
• Experience at vertical SaaS or product-focused software companies preferred
• Staff Engineer or Senior Engineer ownership experience strongly preferred
• Demonstrated ability to operate independently in ambiguous, high-growth environments

Technical Requirements

• Strong backend engineering fundamentals
• Deep expertise in distributed systems architecture
• Experience with concurrency, asynchronous processing, queues, workers, and caching
• Strong production systems and backend platform engineering experience
• Experience designing scalable APIs and service contracts
• Hands-on experience building AI/ML platforms, LLM applications, or autonomous AI agents
• Experience building multi-step agent workflows or orchestration systems
• Strong system design and backend architecture fundamentals
• Experience with observability, debugging, reliability, and production operations
• Comfortable leveraging modern AI development tools to improve engineering productivity

Education

• Bachelor's degree in Computer Science, Software Engineering, or related technical field preferred
• Strong technical foundation with demonstrated engineering excellence

Soft Skills

• High ownership mentality
• Excellent communication and technical leadership skills
• Comfortable operating in ambiguity
• Strong systems thinking and architectural problem-solving
• Independent execution with minimal management
• Bias toward action and shipping
• Strong engineering craftsmanship
• Startup mentality
• Ability to raise engineering quality across the team

Preferred Backgrounds

• AI infrastructure startups
• AI agent platform companies
• Vertical SaaS companies
• Backend platform engineering organizations
• Enterprise AI startups
• Distributed systems organizations
• Workflow automation platforms
• Early-stage venture-backed startups
• Founding engineering teams
• Engineers building production AI platforms

Compensation & Benefits

• Base Salary: $200,000 – $250,000
• Performance Bonus
• Competitive Equity Package
• Significant ownership over AI platform architecture
• Direct collaboration with engineering leadership
• Opportunity to build large-scale autonomous AI systems
• High-impact engineering role
• Exposure to cutting-edge AI agent technologies
• Rapid career growth opportunities
• Hybrid collaboration with a high-performing engineering team

Why Join

This is an opportunity to build the backend platform powering one of the fastest-growing autonomous AI products in production.

You'll architect distributed backend infrastructure, build production AI agent systems, and solve challenging large-scale engineering problems while working alongside an experienced team building enterprise-grade AI technology.

As one of the senior platform engineers, you'll have outsized influence over backend architecture, engineering culture, and technical direction while building AI-native infrastructure deployed across millions of real-world users.