Staff Backend Engineer

Town; San Francisco (CA); On-site; USD 120,000 - 160,000; Full time

Job summary

Town is looking for a foundational backend engineer in San Francisco, CA, to build and scale its AI-native assistant. You'll work on innovative projects that involve LLM infrastructure and agentic systems while influencing architecture decisions directly.

The role is situated in the Financial District, requiring in-person attendance five days a week. Ideal candidates should thrive in fast-paced environments and have experience with AI workloads in production.

Qualifications

• Experience scaling backend systems through high-growth phases.
• Ability to define technical direction in fast-moving environments.
• Familiarity with distributed systems, data pipelines, and APIs.

Responsibilities

• Build orchestration layer for workflows.
• Develop multi-provider LLM infrastructure.
• Design identity and knowledge layer.

Skills

Backend system scaling

Distributed systems

Infrastructure-level problem solving

AI-native coding workflow

LLM infrastructure

Real-time AI workloads

Job description

About Town

Town is an AI-powered assistant that connects to your tools to do real work on your behalf -- triaging your inbox, drafting in your voice, managing your schedule, and running workflows across everything you use. It knows you deeply and gets sharper over time.

About the Role

The core technical challenge at Town is: context from everywhere, action anywhere. The assistant pulls from your email, calendar, Slack, docs, and connected tools to build a deep understanding of who you are and what you need -- then executes reliably across all of them.

Town's AI assistant goes beyond a solid harness and decent tool integrations. It has memory that compounds over time, a suggestion engine that discovers what to automate before you think to ask, and network effects where your assistant gets better because your colleagues are using Town too. These are the systems you'll build.

You'll be a foundational hire, working across the full backend -- from LLM orchestration and workflow execution to the identity and knowledge layer that makes every interaction smarter than the last. Everyone has direct influence over architecture decisions. There's no platform team to hand things off to -- you own it end to end. The environment is greenfield, and the problems are unlike traditional backend engineering: non-deterministic, cost-sensitive LLM workloads; real-time personalization across a growing knowledge graph; agent-to-agent protocols that work across organizational boundaries.

Example projects include...

• Building the orchestration layer for agentic workflows
• Building multi-provider LLM infrastructure
• Rethinking email, calendar, and contacts as AI-native experiences
• Designing the identity and knowledge layer
• Architecting agent networks
• Building the trust and autonomy system
• Defining what service ownership

You might thrive in this role if you...

• Have built and scaled backend systems through a company's high-growth arc -- you were there during the inflection, not after. We want to hear all your concrete product scaling stories.
• Are comfortable defining technical direction in ambiguous, fast-moving environments -- not just executing within one
• Think in systems -- distributed systems, data pipelines, APIs, reliability. You're drawn to infrastructure-level problems and the tradeoffs that come with them.
• Have tuned your AI-native coding workflow that makes you dramatically faster and more effective.
• Have experience with LLM infrastructure, agentic systems, or real-time AI workloads in production
• Care about trajectory over tenure. We're less interested in years of experience than how fast you got here and what you built along the way.
• Are excited about working in-person in SF, five days a week. We believe it matters at this stage.

Location

San Francisco, CA -- five days a week in-person at our Financial District office (near Montgomery BART stop).