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

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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.

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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

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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

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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

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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.

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