Senior Software Engineer

ITSearch · Recruitment agency

Full-time•Full-stack•€90k-110k/year (EUR)•Ireland · Remote within Ireland · Hybrid

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TechJobs.ie Job Insights

At a glance

Employment type: Full-time
Location: Ireland · Remote within Ireland · Hybrid
Workplace: Hybrid · 1 day in office
Salary: €90k-110k/year (EUR)
Category: Full-stack

Technologies & skills

Primary technologies

Python

Cloud & infrastructure

AWS

Other technical skills

LLMs

What you'll be doing

Senior Software Engineer role in Dublin (hybrid, 1 day/week in office) with a focus on backend services, distributed systems, event-driven architecture, and cloud infrastructure. Hands-on engineering with strong emphasis on system design, scalability, reliability, and architectural decisions.

Key requirements

Must-have

Strong Python engineering experience
Proven experience building and delivering cloud-based products
Strong AWS experience (other cloud backgrounds considered)
Experience building serverless applications (particularly AWS Lambda)
Solid understanding of microservices, distributed systems, and event-driven architecture
Experience working with APIs, databases, messaging, and cloud infrastructure
Comfortable owning technical design decisions and implementation details
Strong engineering fundamentals around scalability, reliability, observability, and performance

Nice-to-have

Exposure to LLM integration and AI engineering

Role signals

Technical focus: backend
Leadership: Mentoring
Architecture / system design: Indicated in the listing
Hands-on vs management: Hands-on

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Full job description

Senior Software Engineer

Dublin City Centre

Hybrid – 1 day per week in the office

€90,000 – €110,000 + pension + equity

IT Search has exclusively partnered with a growing connected technology company that builds smart applications and digital experiences at scale.

They’re looking for a Senior Software Engineer to join their platform team, working across distributed services, event-driven architecture and cloud infrastructure.

This is a hands-on engineering role with a strong focus on system design and architecture. You’ll be designing and building backend services, shaping how services communicate, and making the architectural trade-offs that keep systems scalable, reliable and cost-effective.

What they’re looking for:

Strong Python engineering experience
Proven experience building and delivering cloud-based products
Strong AWS experience, although other cloud backgrounds will be considered
Experience building serverless applications, particularly AWS Lambda
Solid understanding of microservices, distributed systems and event-driven architecture
Experience working with APIs, databases, messaging and cloud infrastructure
Exposure to LLM integration and AI engineering is highly desirable
Comfortable owning technical design decisions and getting into the detail of implementation
Strong engineering fundamentals around scalability, reliability, observability and performance

You’ll work closely with the platform engineering team, reporting into the Engineering Manager, with plenty of scope to influence architecture, improve shared engineering practices and mentor other engineers.

If this sounds like your next step, apply via the link or contact Graeme King at IT Search for a confidential chat.

Apply Now

Interview prep pack

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

Your interview focus

Based on this listing, the Senior Software Engineer role focuses on designing and building scalable backend services using Python and AWS, with an emphasis on distributed systems, event-driven architecture, and hands-on technical leadership.

Hands-on backend engineering·Medium
Cloud and serverless architecture·High
Distributed systems design·High
Technical leadership and mentoring·High

Only have 30 minutes?

Follow a focused preparation plan based on this job.

Start 30-minute prep

Your 30-minute plan

Review Python Backend Projects
0–7 min
Select 1-2 relevant projects where you designed or built scalable backend services in Python, and prepare concise summaries.
Refresh AWS and Serverless Knowledge
7–14 min
Revisit your experience with AWS, especially Lambda and related services, and outline key architectural decisions and outcomes.
Prepare Distributed Systems Examples
14–20 min
Identify examples of microservices or event-driven architectures you have worked on, focusing on scalability and reliability.
Reflect on Technical Leadership
20–25 min
Think of situations where you owned technical decisions or mentored others, and prepare to discuss your approach and results.
Draft Role-Specific Questions
25–30 min
Write down 2-3 thoughtful questions about the team, technical challenges, and future direction to ask during the interview.

Likely questions

Expand all

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

1Can you describe a recent project where you designed and implemented a scalable backend service using Python?High
Why they may ask
Assesses your hands-on Python engineering skills and ability to deliver robust backend solutions.
Prepare to discuss
- Clear description of the problem and requirements.
- Explanation of architectural choices and trade-offs.
- Details on scalability, reliability, and performance considerations.
- Reflection on lessons learned or improvements made.
Tip: Use the STAR method (Situation, Task, Action, Result) to structure your answer.
2How have you leveraged AWS services, particularly Lambda, to build serverless applications?High
Why they may ask
Evaluates your practical experience with AWS and serverless patterns.
Prepare to discuss
- Specific AWS services used and why.
- Challenges faced and how you addressed them.
- Impact on scalability, cost, and maintainability.
- Any monitoring or observability strategies implemented.
Tip: Mention both successes and any pitfalls you encountered.
3What are the key considerations when designing a microservices-based, event-driven architecture?High
Why they may ask
Tests your understanding of distributed systems and architectural best practices.
Prepare to discuss
- Discussion of service boundaries and communication patterns.
- Approaches to data consistency and eventual consistency.
- Strategies for observability, monitoring, and error handling.
- Examples of tools or frameworks used.
Tip: Relate your answer to real-world scenarios you've encountered.
4Describe a time when you owned a critical technical decision. How did you approach it and what was the outcome?Medium
Why they may ask
Assesses your leadership, ownership, and decision-making skills.
Prepare to discuss
- Clear context and decision to be made.
- Stakeholder involvement and communication.
- Analysis of options and rationale for your choice.
- Reflection on the impact and any follow-up actions.
Tip: Highlight both technical and interpersonal aspects.
5How do you ensure the reliability and observability of distributed systems you build?Medium
Why they may ask
Focuses on your engineering fundamentals and operational mindset.
Prepare to discuss
- Use of monitoring, logging, and alerting tools.
- Design patterns for fault tolerance and recovery.
- Examples of detecting and resolving production issues.
- Continuous improvement practices.
Tip: Mention specific tools or frameworks if possible.
6Have you integrated APIs, databases, and messaging systems in cloud environments? What challenges did you face?Medium
Why they may ask
Evaluates your practical integration experience and problem-solving skills.
Prepare to discuss
- Types of APIs, databases, and messaging systems used.
- Integration patterns and security considerations.
- Challenges such as latency, consistency, or scaling.
- How you resolved or mitigated these issues.
Tip: Be specific about technologies and outcomes.
7What experience do you have with LLM integration or AI engineering in production systems?Lower
Why they may ask
Assesses your exposure to AI technologies, which is highly desirable for this role.
Prepare to discuss
- Description of the AI/LLM use case.
- Technical approach to integration.
- Challenges around performance, cost, or reliability.
- Results and business impact.
Tip: If you lack direct experience, discuss related work or your approach to learning new AI technologies.

Talking points

Python Engineering for Scalable Backends
Demonstrate your ability to build robust, maintainable backend services using Python, highlighting past projects where you solved complex problems.
AWS and Serverless Application Development
Showcase your experience with AWS services, especially Lambda, and discuss how you've leveraged serverless patterns for scalability and cost-effectiveness.
Microservices and Event-Driven Architecture
Prepare examples of designing or maintaining distributed systems, focusing on how you ensured reliability, scalability, and effective service communication.
Technical Decision-Making and Mentoring
Be ready to discuss situations where you owned architectural decisions, influenced engineering practices, or mentored team members.
API, Database, and Messaging Integration
Highlight your experience integrating APIs, working with databases, and implementing messaging solutions in cloud environments.
Exposure to LLM Integration and AI Engineering
If applicable, prepare to discuss any experience integrating large language models or AI components into production systems.

What to research

Python Backend Engineering
Review your experience building scalable backend services in Python, focusing on system design, performance, and maintainability.
AWS and Serverless Patterns
Refresh your knowledge of AWS services, especially Lambda, and be ready to discuss serverless architectures you have implemented.
Distributed Systems and Event-Driven Design
Prepare examples of designing or maintaining microservices and event-driven systems, including architectural trade-offs and reliability strategies.
Technical Leadership and Mentoring
Reflect on times you have owned technical decisions or mentored others, and be ready to discuss your approach and impact.

Questions to ask

How does the platform team collaborate with other engineering teams and stakeholders?
Why ask this? To understand cross-team communication and influence on architecture.
What are the biggest technical challenges currently facing the platform?
Why ask this? To gauge the complexity and scope of problems you would help solve.
How is architectural decision-making handled within the team?
Why ask this? To clarify your potential role in shaping system design and standards.
What opportunities exist for mentoring or influencing engineering practices?
Why ask this? To assess the scope for leadership and professional growth.
How does the team approach observability and reliability in distributed systems?
Why ask this? To understand the maturity of operational practices and tooling.
Is there an active roadmap for integrating AI or LLM technologies into the platform?
Why ask this? To learn about future technical directions and opportunities to work with AI.

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Apply NowApply before: 15 Oct 2026

Senior Software Engineer

TechJobs.ie Job Insights

At a glance

Technologies & skills

What you'll be doing

Key requirements

Role signals

Similar jobs

Full job description

Interview prep pack

Your interview focus

Only have 30 minutes?

Your 30-minute plan

Likely questions

Talking points

What to research

Questions to ask

Register now to upload your CV

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