Senior & Staff Backend Engineer, AI Systems

We’re hiring a Senior / Staff Backend Engineer to help build a rapidly expanding suite of AI-native products and infrastructure at a high-growth, venture-backed platform.

This role is ideal for someone who stays close to the evolving AI landscape and can distinguish between durable tools and short-lived hype. You’ve built and shipped systems involving large language models—whether in production or as side projects—and you’re comfortable working in environments where APIs, SDKs, and best practices evolve quickly.

The broader mission is to dramatically increase the earning potential and scalability of independent operators in a traditionally relationship-driven industry. Where individuals have historically hit a ceiling early without adding headcount, this platform aims to enable highly leveraged, solo-first operations through intelligent automation. The current focus is an embedded AI copilot that handles complex, time-consuming workflows—freeing users to focus on high-value activities like client relationships, strategy, and growth.

This role spans challenges across the applied AI stack, including building internal tooling that safely exposes core systems to AI agents, improving orchestration layers for reliability and performance, and developing evaluation and observability systems for non-deterministic behavior.

What You’ll Work On

• Partner with product and design to translate ambiguous ideas into production-ready AI capabilities.
  

• Design and build internal tooling that allows AI systems to interact with core data and services in a secure, permission-aware way.
  

• Develop and refine agent orchestration systems, including tool usage, multi-step workflows, retries, and streaming interactions.
  

• Improve system reliability through evaluation frameworks, regression testing, tracing, and metrics to monitor output quality and detect drift.
  

• Optimize for performance and latency in real-time AI interactions.
  

• Collaborate across backend, platform, and frontend layers to deliver cohesive, end-to-end solutions.
  

• Own features from concept through production and iteration.
  

• Help define emerging best practices for applied AI within a scaling engineering organization.
  

Requirements

• Degree in Computer Science or equivalent practical experience.
  

• 5+ years of backend engineering experience.
  

• 3+ years working with Python and modern web frameworks.
  

• Strong experience designing APIs and distributed systems.
  

• Solid understanding of relational databases and ORMs.
  

• Demonstrated interest in applied AI and willingness to stay current.
  

• Strong collaboration and communication skills.
  

• Comfortable operating in fast-moving, ambiguous environments.
  

Preferred Experience

• Experience building and shipping LLM-powered features, including tool use, agent workflows, structured outputs, streaming, and retrieval systems.
  

• Familiarity with modern AI tooling ecosystems, including model provider SDKs and agent frameworks.
  

• Experience designing evaluation systems for AI outputs, including offline testing, model-based evaluation, and tracing.
  

• Regular use of AI-assisted development tools.
  

• Experience with asynchronous processing systems and streaming infrastructure.
  

• Cloud experience (e.g., AWS) and container orchestration (e.g., Kubernetes).
  

Compensation & Benefits

• Competitive base salary with equity, calibrated to experience and level.
  

• Flexible paid time off.
  

• Comprehensive health coverage options.
  

• Retirement plan with employer contribution.
  

• Additional benefits supporting wellness, commuting, and long-term security.
  

Work Environment

• Hybrid work model based in a major U.S. city, with a few in-office collaboration days each week.
  

Guiding Principles

• A bias toward innovation over maintaining legacy approaches.
  

• Strong emphasis on collaboration and shared success.
  

• Deep belief in technology as a force multiplier for both individuals and industries.
  

• A service-oriented mindset toward end users.
  

• A balance of ambitious goals with disciplined execution.