Job description

About Loop: Loop AI is an agentic AI platform for the back office of the real economy. Today we build end-to-end agentic workflows for enterprises; our goal is for users to build and manage agents themselves. Founded in 2022, we're trusted by 300+ brands powering thousands of locations across the US, backed by a $14M Series A led by Nyca Partners, with teams in New York, San Francisco, Tampa, and Bengaluru.

We're built by a world-class team. Several of us are ex-founders who scaled our own companies to multiple millions in ARR before joining hands at Loop to execute on a bigger shared vision — alongside operators and AI engineers from Stanford, Harvard, Wharton, Uber, Google, Amazon, and McKinsey.

We believe agentic products are the future of the software–human interface, and restaurants were only the beginning. Flat hierarchy, lean high-impact team, radical ownership, no bureaucracy — this is your chance to help steer the rocketship.

About the Role: As an SDE-2, you own execution end to end: scoping the requirement, jamming on system design, shipping it, and running it in production. You'll find the solution to the customer problem and implement it, rather than receiving scoped tasks.

Our stack is agent-native, so most of your work sits in AI agentic systems, orchestration and tool-calling, agentic data pipelines, long-running workflows that have to be repeatable and idempotent, and the distributed services that feed them. Product thinking matters here, you will shape scope with Product, work closely with senior engineers on system design, and own the outcome rather than a ticket. Problems arrive as conversations and ideas, and you are expected to shape, scope & implement them from 0->1.

We hire for end-to-end ownership, product curiosity, and the hunger to keep learning and raise the bar.

Key Responsibilities:

Build Products End to End: Analyze, scope, and implement product features and APIs with clean, maintainable, well-tested code. Take problems from requirement to production with increasing independence.

Implement AI agent workflows: Build and integrate LLM-powered agentic features: tool/function calling, prompt orchestration, retrieval, and the guardrails that keep autonomous actions safe and auditable.

Feed the agents: Develop & manage ingestion streams, ETL pipelines, and the data architectures that give agents the data they need to automate workflows, and execute operational tasks.

Own the cloud data stack: Build and run services on GCP with data based transformations, and own the infrastructure and deployment paths for what you ship.

What We're Seeking:

3+ years of full-time experience building and shipping production backend systems and web applications

Strong fundamentals in data structures, algorithms, and system architecture. You can design a system and defend the tradeoffs.

Real experience building data pipelines — event-driven, batch or streaming — and owning their correctness, cost and failure modes.

Familiarity with the agent stack: model APIs, prompt orchestration, tool-calling, retrieval, and how you tell whether the agent is actually right.

Hands-on with agentic application development: model APIs, prompt design, and tool-calling patterns. You also code with AI tools daily without dropping the bar on correctness and review.

Comfort with cloud services , event-driven architectures, exposure to BI or analytics platforms is a plus.

Product thinking and 0-to-1 experience. You work directly with product folks across functions and geographies, shape scope when the spec is a conversation, and debug and optimize what you own without waiting to be asked

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