Principal Software Engineer – Greenfield AI Platform!

Archer · Recruitment agency
Full-time•Platform / Infrastructure•Dublin, Ireland
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At a glance

Employment type
Full-time
Workplace
On-site

Technologies & skills

Other technical skills

LLMs

What you'll be doing

Principal Software Engineer role for a greenfield AI platform at a global SaaS company in Dublin. Involves hands-on coding, technical leadership, architectural influence, and mentoring. Focus on building scalable cloud-native systems, AI agents, and LLM-powered workflows in a modern SaaS environment.

Key requirements

Must-have

  • 7+ years of software engineering experience, ideally in SaaS or product-led environments
  • Strong hands-on experience with TypeScript, JavaScript, Node.js, Python and modern frameworks
  • Proven experience designing scalable cloud-native systems and microservices
  • Practical experience building AI agents, integrating LLMs or applying AI-assisted engineering workflows

Experience: 7+ years

Role signals

Technical focus
software engineering, cloud technology, AI innovation
Leadership
Mentoring
Architecture / system design
Indicated in the listing
Hands-on vs management
Hands-on

Full job description

Principal Software Engineer – Greenfield AI Platform!

Ready to shape the future of software engineering with AI at the core?

I’m partnering with an innovative global SaaS organisation in Dublin, looking for a Principal Software Engineer to help drive the next generation of cloud-based products.

This is a chance to go beyond traditional software development and help redefine how engineering teams build software using AI. You’ll combine hands-on coding, technical leadership and architectural influence, designing scalable cloud solutions while exploring AI agents, LLM-powered workflows and intelligent automation across the software development lifecycle.

Working alongside talented engineers and product leaders, you’ll have a genuine voice in technical strategy, influence engineering standards and mentor the next generation of developers. From shaping system architecture to bringing AI-driven capabilities into production, you’ll play a key role in turning ambitious ideas into real-world products.

What makes this opportunity exciting?

  • Greenfield development and the opportunity to shape modern SaaS products.

  • AI at the heart of engineering, including agentic systems and LLM-powered solutions.

What we’re looking for:

  • 7+ years of software engineering experience, ideally in SaaS or product-led environments.

  • Strong hands-on experience with TypeScript, JavaScript, Node.js, Python and modern frameworks.

  • Proven experience designing scalable cloud-native systems and microservices.

  • Practical experience building AI agents, integrating LLMs or applying AI-assisted engineering workflows.

If you’re excited about the intersection of software engineering, cloud technology and AI innovation, this is an opportunity to make a real impact.

Send your CV to

For a confidential chat: (01) 649 8531

Interview prep pack

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

Your interview focus

Based on this listing, the Principal Software Engineer role centers on leading the design and development of a greenfield AI-driven SaaS platform, with a strong emphasis on hands-on coding, cloud-native architecture, and integrating AI/LLM technologies.

  • Cloud-native architecture expertise·High
  • AI/LLM integration experience·High
  • Technical leadership and mentoring·High
  • Hands-on coding skills·High

Only have 30 minutes?

Follow a focused preparation plan based on this job.

Start 30-minute prep

Your 30-minute plan

  1. Review Recent Cloud-Native Projects

    0–7 min

    Select 1-2 examples where you designed or led scalable cloud systems, focusing on architecture and outcomes.

  2. Prepare AI/LLM Integration Stories

    7–14 min

    Identify concrete instances where you built or integrated AI agents or LLMs, noting challenges and results.

  3. Refresh on TypeScript, Node.js, and Python

    14–20 min

    Review code samples and be ready to discuss technical decisions and best practices.

  4. Summarize Leadership and Mentoring Experience

    20–25 min

    Outline key mentoring moments and how you influenced engineering standards or team growth.

  5. Draft Role-Specific Questions

    25–30 min

    Prepare thoughtful questions about the platform, team, and AI strategy to ask during the interview.

Likely questions

, 6 items

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

Talking points

, 5 items

  • Designing Scalable Cloud-Native Systems

    Demonstrate your experience architecting robust, scalable solutions in SaaS or product-led environments.

  • Hands-on Coding with Modern Languages

    Showcase your proficiency in TypeScript, JavaScript, Node.js, and Python, as these are core to the stack.

  • Building and Integrating AI Agents/LLMs

    Highlight practical examples where you have implemented AI agents or leveraged LLMs to enhance engineering workflows.

  • Technical Leadership and Mentoring

    Provide evidence of your ability to influence technical strategy, set engineering standards, and mentor teams.

  • Driving AI-Driven Product Innovation

    Illustrate how you have contributed to or led initiatives that brought AI-powered features into production.

What to research

, 4 items

  • Review Cloud-Native Architecture Patterns

    Refresh your knowledge of designing scalable, resilient systems using cloud services and microservices.

  • Deepen Understanding of LLMs and AI Agents

    Prepare examples of integrating large language models or AI agents into production systems.

  • Hands-on with TypeScript, Node.js, and Python

    Be ready to discuss and demonstrate your experience with these languages and related frameworks.

  • Mentoring and Technical Leadership

    Gather stories and outcomes from your experience mentoring engineers and influencing technical direction.

Questions to ask

, 6 items
  1. What are the main technical challenges you anticipate for this greenfield AI platform?

    Why ask this? Shows your interest in the project's complexity and readiness to tackle key issues.

  2. How does the team currently approach integrating AI and LLMs into the development lifecycle?

    Why ask this? Clarifies the maturity of AI adoption and your potential impact.

  3. What is the expected balance between hands-on coding and architectural leadership in this role?

    Why ask this? Helps you understand day-to-day responsibilities and expectations.

  4. How is technical strategy and decision-making shared between engineering and product leadership?

    Why ask this? Assesses collaboration and influence opportunities.

  5. What opportunities exist for mentoring and growing the engineering team?

    Why ask this? Demonstrates your commitment to leadership and team development.

  6. How do you measure the success of AI-driven features in your products?

    Why ask this? Shows your focus on impact and continuous improvement.

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Apply NowApply before: 20 Nov 2026