Senior Engineer – Backend & Platform

Location - Remote (US & Canada) — Periodic Travel to San Francisco, CA or Toronto, Canada for Team Collaboration

Compensation - $190,000 – $300,000 Base + Meaningful Founding-Level Equity

Visa - Strong Preference for Candidates with Existing US or Canadian Work Authorization

Visa Sponsorship May Be Considered for Exceptional Candidates

Company Stage - Seed Stage (~$5M Raised)

Industry - AI Infrastructure, Enterprise AI, LLM Agents, Platform Engineering, Knowledge Systems

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About the Company

The company is building an AI-native infrastructure platform that enables LLM agents to reason over large-scale organizational knowledge, making enterprise information more accessible, actionable, and intelligent.

Already deployed with enterprise customers ranging from hundreds to thousands of employees, the platform powers complex AI workflows that combine distributed systems, large language models, retrieval systems, and production-grade backend infrastructure to solve real-world enterprise problems.

Backed by leading venture investors and built by an experienced founding team, the company is assembling a small, high-talent-density engineering organization where every engineer owns foundational architecture and directly influences product direction.

As one of the earliest Backend & Platform Engineers, you'll architect and build the core infrastructure powering AI agents, distributed backend services, and enterprise-scale knowledge systems while working directly with the founders on some of the company's most important technical challenges.

This is a rare opportunity to join an early-stage AI infrastructure company where you'll own high-impact technical decisions, shape engineering culture, and build foundational systems supporting the next generation of enterprise AI.

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What You'll Do

• Architect and build the company's core backend and platform infrastructure
• Design scalable distributed systems supporting enterprise AI workloads
• Build reliable APIs, backend services, and platform capabilities from the ground up
• Design and implement LLM agents capable of reasoning over complex organizational data
• Build production-grade retrieval, memory, and knowledge infrastructure for AI systems
• Own architecture decisions across backend services, data infrastructure, and platform engineering
• Design scalable SQL data models and backend storage systems
• Improve system reliability, scalability, observability, and operational excellence
• Partner closely with founders on technical strategy and long-term platform architecture
• Own high-impact engineering initiatives from design through production deployment
• Help establish engineering standards, architecture principles, and platform best practices
• Operate with high autonomy while solving complex enterprise-scale technical challenges

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Ideal Candidate Background

Experience Requirements

• 5+ years of experience in backend or platform engineering
• Experience owning production backend systems operating at meaningful scale
• Experience leading technical architecture for high-impact engineering projects
• Experience working at high technical-bar engineering organizations or early-stage startups
• Experience building distributed systems used by real customers
• Experience operating with high ownership and minimal oversight
• Founding Engineer or early startup experience strongly preferred
• Experience designing production platform architecture preferred
• Demonstrated ability to lead ambiguous technical initiatives end-to-end

Technical Requirements

• Deep Python engineering expertise
• Strong distributed systems and backend architecture experience
• Experience designing production APIs and backend platform services
• Strong SQL and relational database experience
• Experience building scalable platform infrastructure
• Hands-on experience with LLMs, RAG systems, AI agents, or agentic workflows
• Strong system design fundamentals
• Experience with observability, debugging, and production operations
• Familiarity with AI-native infrastructure and enterprise knowledge systems
• Strong engineering judgment and architectural decision-making
• Experience leveraging AI coding tools effectively while maintaining engineering quality

Education

• Bachelor's degree in Computer Science, Software Engineering, or related technical field preferred
• Strong academic background from a top engineering program preferred

Soft Skills

• High ownership mentality
• Excellent communication and technical leadership skills
• Comfortable operating in ambiguity
• Strong systems thinking and problem-solving abilities
• Independent execution with minimal management
• Bias toward action and shipping
• Strong engineering craftsmanship
• Startup mentality
• Ability to mentor and elevate engineering standards

Preferred Backgrounds

• AI infrastructure startups
• Platform engineering organizations
• Backend infrastructure teams
• Enterprise AI startups
• LLM platform companies
• Distributed systems organizations
• Developer infrastructure companies
• Early-stage venture-backed startups
• Founding engineering teams
• Engineers building AI-native backend platforms

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Compensation & Benefits

• Base Salary: $190,000 – $300,000
• Meaningful Founding-Level Equity
• Significant ownership over backend architecture
• Direct collaboration with founders
• Opportunity to shape foundational AI infrastructure
• Remote-first work environment
• Periodic onsite collaboration with engineering team
• Health Insurance
• Flexible PTO
• Transportation and wellness benefits
• Rapid career growth opportunities

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Why Join

This is an opportunity to build the foundational infrastructure powering the next generation of enterprise AI systems.

You'll architect distributed backend platforms, build intelligent LLM agents, and solve challenging large-scale systems problems while working directly alongside an experienced founding team.

As one of the earliest platform engineers, you'll have outsized ownership over architecture, engineering culture, and product direction while building AI-native infrastructure deployed in real enterprise environments.