AI Infrastructure Engineer

About the Company

Fin builds AI customer agents that help businesses deliver strong support experiences across the full customer journey, including service, sales, and ecommerce. The company’s AI agent works end to end across channels with minimal setup, and can be paired with Fin’s help desk to create a unified support system for modern teams. Established in 2011, Fin has grown into one of the fastest-scaling companies in its space and serves nearly 30,000 businesses worldwide.

Role Overview

This senior-level opportunity is for an AI Infrastructure Engineer who will help build the platforms that train and serve the company’s next generation of AI products. The work spans the stack from GPU-level optimization through to production systems that support millions of customer queries each month.

You will join a compact, deeply technical team focused on modern AI infrastructure. The group has already built training pipelines and inference systems for custom models such as Fin Apex, which is positioned as a high-performing model for customer service tasks.

What You Will Do

• Design, implement, and scale training pipelines for large transformer and LLM models, covering data ingestion, preprocessing, distributed training, and evaluation.
• Develop and improve inference services that provide fast, dependable customer experiences, including autoscaling, routing, and fallback logic.
• Work on performance at the GPU layer by tuning kernels, improving hardware utilization, and finding bottlenecks across the training and serving stack.
• Partner with machine learning scientists to productionize new training and inference techniques.
• Contribute to hiring, mentoring, and the growth of engineers on the team.
• Help raise technical standards, reliability, and operational excellence across the AI platform.

Who We Are Looking For

This role is aimed at senior candidates, and the following background is a strong match rather than a rigid checklist.

• At least 5 years of software engineering experience, with a proven record of delivering high-quality products or platforms.
• A degree in Computer Science, Computer Engineering, or a similar field, or equivalent experience backed by strong fundamentals.
• Practical experience in one or more of these areas: model training for transformers or LLMs, model inference at scale, or low-level GPU development using CUDA or Triton.
• Comfort operating in production environments with meaningful scale in traffic, data, or organizational complexity.
• Strong communication skills with the ability to explain technical ideas clearly to different audiences.
• A solid engineering foundation, curiosity, and a willingness to keep learning and improving.
• Deep knowledge of at least one programming language such as Python, Ruby, Java, or Go, with an emphasis on clean, reliable code and fast adaptation to new systems.

Nice-to-Have Experience

• Background at AI-native companies that train and/or serve their own models.
• Experience running training or inference workloads on Kubernetes.
• Familiarity with AWS or another major cloud provider.
• Production experience using Python in machine learning or infrastructure work.
• Evidence of genuine technical interest through side projects, open source, meetups, or writing about your work.

Benefits

• Competitive compensation along with equity in a fast-growing startup.
• Lunch served every weekday, plus snacks and a fully stocked kitchen.
• Regular pay reviews tied to performance.
• Unlimited access to Claude Code and other leading AI tools, with experimentation actively encouraged.
• Pension scheme with employer match of up to 4%.
• Life assurance, plus comprehensive health and dental cover for you and your dependents.
• Flexible paid time off.
• Paid maternity leave and 6 weeks of paternity leave.
• Cycle-to-Work Scheme support, including secure bike storage.
• MacBooks as standard, with Windows available for certain roles where required.

Working Policy

This is a hybrid position based in Dublin, County Dublin, Ireland. Employees are expected to be in the office at least three days per week, with flexibility to work from home on the remaining days.

Culture and Equal Opportunity

Fin describes its culture as open, inclusive, and focused on collaboration. The company avoids divisive topics in internal and external communications to maintain a safe and cohesive work environment, while respecting personal opinions and expression on personal time and personal social platforms. Fin is committed to equal employment opportunity and does not discriminate on the basis of race, color, religion, creed, national origin, ancestry, sex, gender, age, disability, veteran or military status, genetic information, sexual orientation, gender identity, gender expression, marital status, or any other protected characteristic under applicable law.