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Staff Backend Engineer

Join Town as a Staff Backend Engineer to build AI-powered systems that enhance productivity through intelligent workflows.

Location
NYC
Compensation
Not disclosed
Level
staff
Type
full time · On-site

Posted by employer 1 month ago

First seen on Joblaze 1 week ago

Last verified on the company career page 1 day ago

Apply at Town → Save job Scanned from town.com

Skills & Technologies

AI in the day-to-day

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.

Not disclosed in this posting: compensation, years of experience, visa sponsorship.

Joblaze summary

In this role, the Staff Backend Engineer at Town will tackle complex challenges by building and optimizing backend systems that integrate AI-driven workflows across various tools. Key skills include experience with LLM infrastructure, distributed systems, and real-time AI workloads, as well as a strong ability to define technical direction in fast-paced environments. This position is ideal for someone with a proven track record in scaling backend systems during high-growth phases and a passion for infrastructure-level problem-solving. Town emphasizes a collaborative, in-person work culture, making it a fitting environment for those who thrive in dynamic settings.

Joblaze insights

Quick facts

Is the Staff Backend Engineer role remote?
No — this is an on-site role in NYC.
Where is the role based?
Town is hiring for this position in NYC.
What's the tech stack?
Joblaze extracted these technologies from the posting: AI/ML, LLM, infrastructure.
What seniority level is this role?
Town targets staff-level candidates for this position.
Is this full-time or contract?
Full-time for this Staff Backend Engineer role at Town.

From the original posting

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 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, five days a week. We believe it matters at this stage.

 

Location

5 days per week in person, in either SF or NYC

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