Skip to main content

Engineering Manager, AI Models Infrastructure

Intercom
Hybrid - Dublin, Ireland; in office at least three days per weekUpdated 23d ago
Compensation
Not disclosed
Location
Hybrid - Dublin, Ireland; in office at least three days per week
Remote eligibility
Employment
Full-time
Lead / Manager
Role family
Engineering
AI / ML
Apply on job-boards.greenhouse.io
Job actionsApply now
Job actionsApply now

About the job

Engineering Manager, AI Models Infrastructure

Fin is the AI Customer Agent company on a mission to help businesses provide perfect customer experiences. Our AI Agent Fin is the highest-performing AI Customer Agent on the market today, enabling businesses to deliver impeccable, always-on customer support across the customer journey – from service, to sales, to ecommerce. Powered by our own AI models, Fin resolves complex customer issues end-to-end across every channel, with minimal set-up and integration. Fin can also be combined with our natively integrated Intercom help desk for one single system that is designed to meet the needs of modern day support teams. Founded in 2011, Fin became one of the fastest growing companies and remains one of the largest private software companies in the world with nearly 30,000 global businesses using our products to transform their customer support.

Opportunity

We’re hiring an Engineering Manager for our AI Models Infrastructure Team in the AI Group. The AI Models Infrastructure team builds and operates the foundational infrastructure that empowers our teams to train and run Fin's own AI models. This is a highly technical EM role - you’ll lead a team of expert engineers in a fast-evolving technical domain. In order to empower this team to be most effective, you will need prior experience in AI, and the appetite to continually invest in deepening your technical knowledge.

Responsibilities

  • Lead a high-performing team building the platform and infrastructure that power Fin's AI capabilities.
  • Magnify the team’s effectiveness, whether that means removing impediments, or finding ways to accelerate their progress.
  • Support teams of ML Scientists and Engineers building AI powered capabilities.
  • Plan, prioritize, and deliver high-impact roadmaps in partnership with the team’s most senior engineers, balancing delivery, quality, and innovation.
  • Empower the engineers on the team to act with agency and maximize their impact.
  • Expand your scope over time, potentially taking ownership of additional platform domains as the team and AI initiatives grow.

Qualifications

  • Experience training ML models and operating them in production, at scale.
  • Experience leading infra or platform teams.
  • Strong prior experience working as an engineer.
  • Strong technical judgment and communication skills, enabling you to advocate for the team’s needs.
  • Adaptable leadership style suited to a group that will grow quickly, and change shape over time.
  • Curiosity and enthusiasm for AI.

Benefits

  • Competitive salary and equity in a fast-growing start-up.
  • We serve lunch every weekday, plus a variety of snack foods and a fully stocked kitchen.
  • Regular compensation reviews - we reward great work!
  • Pension scheme & match up to 4%.
  • Peace of mind with life assurance, as well as comprehensive health and dental insurance for you and your dependents.
  • Flexible paid time off policy.
  • Paid maternity leave, as well as 6 weeks paternity leave for fathers, to let you spend valuable time with your loved ones.
  • If you’re cycling, we’ve got you covered on the Cycle-to-Work Scheme. With secure bike storage too.
  • MacBooks are our standard, but we also offer Windows for certain roles when needed.

Policies

Fin has a hybrid working policy. We believe that working in person helps us stay connected, collaborate easier and create a great culture while still providing flexibility to work from home. We expect employees to be in the office at least three days per week.

Skills & tags

What you can verify before applying

This older or imported row is missing pay, so treat compensation as unknown until the company confirms it. Remote scope, employment type, source, and the employer apply destination are still shown upfront.