Engineering Manager, AI Models Infrastructure

Intercom
Full-time•Engineering management•Dublin, Ireland · Remote within Ireland
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What you'll be doing

Fin is seeking an Engineering Manager for the AI Models Infrastructure Team to lead expert engineers building and operating foundational infrastructure for training and running Fin's AI models. This highly technical role requires prior AI experience and strong leadership to support ML scientists and engineers in a fast-evolving domain.

  • Lead a high-performing team building platform and infrastructure for AI capabilities
  • Magnify the team’s effectiveness by removing impediments or accelerating progress
  • Support teams of ML Scientists and Engineers building AI powered capabilities
  • Plan, prioritize, and deliver high-impact roadmaps with senior engineers
  • Empower engineers to maximize their impact
  • Expand scope over time, potentially taking ownership of additional platform domains

Key requirements

Must-have

  • Experience training ML models and operating them in production at scale
  • Experience leading infrastructure or platform teams
  • Strong prior experience working as an engineer
  • Strong technical judgment and communication skills
  • Adaptable leadership style for a growing and changing team

Role signals

Technical focus
AI infrastructure, ML model training and operations
Leadership
People management
Architecture / system design
Indicated in the listing
Hands-on vs management
Hands-on

Full job description

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. Driven by our core values, we push boundaries, build with speed and intensity, and relentlessly deliver incredible value to our customers.

Fin is the AI Customer Service company on a mission to help businesses provide incredible customer experiences.

Our AI agent Fin, the most advanced customer service AI agent on the market, lets businesses deliver always-on, impeccable customer service and ultimately transform their customer experiences for the better. Fin can also be combined with our Helpdesk to become a complete solution called the Fin Customer Service Suite, which provides AI enhanced support for the more complex or high touch queries that require a human agent.

Founded in 2011 and trusted by over 30,000 global businesses, Fin is setting the new standard for customer service. Driven by our core values, we push boundaries, build with speed and intensity, and consistently deliver incredible value to our customers.

###What’s the 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.

Learn more about Fin's engineering culture at intercom.engineering, and more about Fin at fin.ai.

###What will I be doing?

You will:

-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.

###What skills do I need?

  • 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.

##Benefits

We are a well treated bunch, with awesome benefits! If there’s something important to you that’s not on this list, talk to us!

#LI-Hybrid

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.

We have a radically open and accepting culture at Fin. We avoid spending time on divisive subjects to foster a safe and cohesive work environment for everyone. As an organization, our policy is to not advocate on behalf of the company or our employees on any social or political topics out of our internal or external communications. We respect personal opinion and expression on these topics on personal social platforms on personal time, and do not challenge or confront anyone for their views on non-work related topics. Our goal is to focus on doing incredible work to achieve our goals and unite the company through our core values.

Fin values diversity and is committed to a policy of Equal Employment Opportunity. Fin will not discriminate against an applicant or employee on the basis of race, color, religion, creed, national origin, ancestry, sex, gender, age, physical or mental disability, veteran or military status, genetic information, sexual orientation, gender identity, gender expression, marital status, or any other legally recognized protected basis under federal, state, or local law.

Interview prep pack

Grounded in this listing. Use it to prepare examples before you apply.

Your interview focus

Based on this listing, the Engineering Manager, AI Models Infrastructure role at Fin focuses on leading a high-performing team responsible for building and operating the foundational infrastructure that powers Fin's AI models, with a strong emphasis on technical leadership, AI/ML expertise, and scalable platform development.

  • Hands-on AI/ML infrastructure experience·High
  • Technical leadership and team empowerment·High
  • Strategic planning and delivery·Medium

Only have 30 minutes?

Follow a focused preparation plan based on this job.

Start 30-minute prep

Your 30-minute plan

  1. Research Fin's AI Engineering Culture

    0–7 min

    Read Fin's engineering blog and company website to understand their approach to AI infrastructure and team values.

  2. Review Your ML Model Operations Experience

    7–14 min

    Prepare concise stories about deploying, monitoring, and scaling ML models in production environments.

  3. Reflect on Leadership and Team Empowerment

    14–20 min

    Identify examples where you led infrastructure/platform teams, empowered engineers, and navigated change.

  4. Prepare Questions for the Interviewers

    20–25 min

    Draft thoughtful questions about team structure, technical challenges, and growth opportunities at Fin.

  5. Review AI Infrastructure Trends

    25–30 min

    Update yourself on current best practices and challenges in AI model infrastructure relevant to customer service applications.

Likely questions

, 7 items

Priority reflects how strongly this topic is emphasised in the job listing, not whether it will be asked.

Talking points

, 5 items
  • Experience with ML Model Training and Production Operations

    You will need to demonstrate your ability to manage the lifecycle of machine learning models at scale, including deployment, monitoring, and optimization.

  • Leading Infrastructure or Platform Teams

    The role requires proven experience in managing technical teams responsible for building and maintaining robust, scalable infrastructure.

  • Technical Judgment and Communication

    Strong decision-making and the ability to advocate for your team's needs are essential for success in this highly technical and collaborative environment.

  • Adaptable Leadership in a Rapidly Evolving Domain

    You should be prepared to discuss how you have led teams through growth and change, especially in fast-moving technical areas like AI.

  • Roadmap Planning and Delivery

    The ability to plan, prioritize, and deliver high-impact projects in partnership with senior engineers is a core responsibility.

What to research

, 4 items
  • Fin's AI Model Infrastructure Approach

    Review Fin's public engineering blog and website to understand their AI infrastructure philosophy and recent projects.

  • Recent Trends in AI Model Operations

    Brush up on best practices and challenges in deploying and operating ML models at scale, especially in customer service applications.

  • Leadership in High-Growth Technical Teams

    Prepare examples of leading teams through rapid growth, change, or technical evolution.

  • Cross-Functional Collaboration with ML Teams

    Think through your experience working with ML scientists and engineers to deliver infrastructure that meets their needs.

Questions to ask

, 6 items
  1. How does the AI Models Infrastructure team collaborate with ML scientists and product engineering teams at Fin?

    Why ask this? To understand cross-team dynamics and expectations for collaboration.

  2. What are the biggest technical challenges currently facing the AI Models Infrastructure team?

    Why ask this? To identify immediate priorities and areas where your expertise can add value.

  3. How does Fin balance innovation with reliability and scalability in its AI infrastructure?

    Why ask this? To learn about the company's approach to technical trade-offs and risk management.

  4. What does success look like for this role in the first 6-12 months?

    Why ask this? To clarify expectations and key performance indicators for the position.

  5. How does the company support ongoing technical learning and growth for engineering managers?

    Why ask this? To assess opportunities for professional development and staying current in AI/ML.

  6. What is the team's approach to roadmap planning and prioritization, especially as the AI initiatives expand?

    Why ask this? To understand how strategic decisions are made and your potential influence on them.

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Apply NowApply before: 5 Nov 2026