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🌐 Remote💼 Full-time🗓 2026-06-25

Core

Orchestrate AI agents to design, implement, and validate backend systems and data services for social analytics in the alcohol industry.

Role type

Senior AI-forward software engineer (system architect)

Builds

Production backend systems, data services, and AI-driven workflows

Domain

Social analytics, alcohol industry SaaS, AI agent orchestration

Deliverable

production ML models | product features | infrastructure

Required skills

AI agent orchestration, system architecture design, code review and validation, workflow decomposition, API design, data extraction strategy

Preferred skills

Experience with Cursor/Claude, MCP tools, AI-driven development patterns

Technologies

Claude, Cursor, custom MCP tools

Responsibilities

Design system architectures for AI agents to implement, decompose complex projects into AI-executable tasks, review and validate AI-generated code, build and refine AI workflows, collaborate on AI-driven development best practices, own system outcomes

Seniority

Senior, hands-on IC

Rewrite
## About the role We use social analytics and AI to help suppliers in the alcohol industry optimize sales. Our platform processes billions of data points and delivers insights through a robust SaaS product used by top-tier analysts and global brands. ## About the company We're a fully remote team of 20+ distributed across the US. We care about capability over titles, value outcomes over process, and keep ego to a minimum. We collaborate tightly, move fast, and meet up in person a few times a year to recharge and plan together. We're in the middle of a major shift: transitioning from AI-assisted development (engineers using Cursor and Claude as tools) to AI-forward development (AI agents handling most planning, task management, and implementation under human orchestration). This isn't theoretical—we're actively building production systems this way today. ## What You'll Do - Orchestrate AI agents (Claude, Cursor, custom MCP tools) to design and deliver backend systems and data services - Decompose complex engineering projects into AI-executable tasks, manage workflows, and ensure quality outcomes - Review and validate AI-generated code for correctness, performance, and maintainability - Design system architectures that AI agents will implement—you set the vision, AI does the execution - Build and refine AI workflows for common engineering patterns (data extraction, API development, testing) - Collaborate with AI-assisted teams to establish best practices for AI-driven development - Own outcomes, not code—you're responsible for working systems, not personally writing every line ## A Day in the Life You're tasked with building a new data extraction service. Instead of opening your editor: - You design the architecture—database schema, API contracts, error handling strategy by conversing with a CTO AI - You write specifications for AI agents—clear requirements, edge cases, quality criteria - You orchestrate AI to implement the service—using Cursor/Claude to generate code, tests, and documentation - You review and validate—run tests, check edge cases, ensure it meets production standards - You iterate with AI—refine, optimize, and handle any issues that arise You shipped a production-ready service in a day or two that might have taken a week of hands-on coding. That's AI-forward engineering. ## What This Role Is (and Isn't) This is AI-forward engineering. You'll spend more time designing, directing, and validating than writing code from scratch. You'll work through AI agents to deliver systems at scale and velocity that wouldn't be possible alone. This is not traditional software engineering. If you love being in the editor all day writing every line yourself, this isn't the role. If the idea of delegating implementation to AI makes you uncomfortable, we're not there yet together. This requires strong engineering judgment. You need to know what good looks like.
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