Engineering Manager

TL;DR

Engineering Manager (Data Platforms): Scaling a gamified data collection platform and growing the engineering organization to support rapid growth with an accent on maintaining high technical quality and hands-on involvement. Focus on balancing short-term commercial contracts with long-term platform investments, leading technical direction, and ensuring quality delivery under tight SLAs.

Location: Onsite in San Francisco

Company

hirify.global is building a gamified data collection platform where contributors take on quests, bounties, and challenges.

What you will do

• Scale the team by hiring 5+ engineers, building interview processes, and creating technical assessments.
• Balance short-term delivery for commercial contracts with long-term platform investments.
• Write code, review design docs, and make system-level architecture decisions.
• Lead technical direction, balancing customer features with platform improvements.
• Build lightweight processes to improve coordination without slowing down velocity.
• Oversee execution for customer contracts with tight SLAs and manage on-call, emergency fixes, and stability.

Requirements

• Strong background as a senior engineer who moved into management.
• Hands-on experience with React, Next.js, and TypeScript.
• Track record of building scalable systems for complex workflows, ideally in developer tooling or data platforms.
• Experience managing 7–20 person teams in high-growth startups.
• Comfort with customer-facing engineering and delivering under tight deadlines.
• Ability to implement right-sized process — structure without bureaucracy.

Nice to have

• Experience scaling from 5 → 20+ engineers at a Series A/B startup.
• Familiarity with marketplaces, two-sided platforms, or developer communities.
• Background in frontier data, ML pipelines, or developer tooling.

Culture & Benefits

• Technically impressive environment where you earn respect from engineers through coding and system design.
• Execution-focused culture that values velocity, stability, and delivery.
• Startup DNA: scrappy, resourceful, and thrives in ambiguity.
• Mission-driven to create the data engine for AI progress.