Top Software Engineer Jobs in Dublin

Lead complex software projects for Toast’s international platform. Design, build, deploy, and maintain resilient, scalable distributed systems; mentor engineers; guide technical discussions; debug multithreaded applications; collaborate with cross-functional teams and pilot customers; and promote engineering best practices. The role requires working across the technology stack and supporting global product launches in a hybrid Dublin office environment.

Leads platform engineering initiatives delivering scalable cloud-native systems and AI-driven applications. Responsibilities include full software lifecycle execution, system design reviews, infrastructure and tooling development, ML framework integration, monitoring, and maintenance. The role mentors engineers, influences technical direction, collaborates cross-functionally on requirements, and drives continuous improvement across distributed systems and platform capabilities.

Provides technical leadership for site reliability engineering across Walmart Data Ventures. Designs scalable automation, observability, SLO tooling, and AI-powered agents for incident triage, root cause analysis, workflow automation, self-healing, and customer support. Establishes reliability standards, improves scalability and resilience, reduces incidents and operational toil, and advances CI/CD, testing, monitoring, debugging, and production readiness through cross-functional engineering influence.

Build and maintain full-stack web products across frontend, backend, databases, DevOps, analytics, and third-party integrations. The engineer will implement features, fix bugs, improve infrastructure, monitoring, deployments, testing, and developer experience, and participate in on-call support. The role requires collaboration with product teams, proactive technical ownership, reliable production code, analytics-informed iteration, and fluency with AI coding tools. Senior candidates may additionally own architecture, technical strategy, and major projects.

Build and maintain Ruby on Rails APIs for internal workflows, from stakeholder discovery and requirements refinement through design, testing, release, and evaluation. Write secure, maintainable code handling authentication, authorization, and sensitive data. Troubleshoot API issues, add regression coverage, participate in design discussions, review code, document decisions, and collaborate asynchronously in a distributed agile team.

Develop production Rust code for managing, reconfiguring, and adapting cloud resources within a Kubernetes development platform. Collaborate on architecture, infrastructure, and feature design; use AI to improve delivery; and work directly with users to gather requirements and debug complex distributed environments. The role requires strong systems thinking, cloud-native infrastructure knowledge, and effective async collaboration in a remote-first startup.

Leads architecture, development, optimization, testing, and delivery of modern C++ 3D software for clinical dental applications. Owns rendering, geometry, APIs, CI/CD, and cross-language integrations while applying AI-assisted development practices. Investigates complex defects, mentors engineers, leads technical discussions, collaborates across product and manufacturing teams, and ensures compliance with medical device software quality processes.

Leads full-stack software engineering for employee communications and collaboration applications, including telephony, meetings, video, and productivity tools. Designs, develops, tests, troubleshoots, and reviews secure production code; improves application resiliency and operational stability; automates recurring remediation; and guides responsible adoption of AI-assisted engineering tools. Evaluates vendor and internal architectural solutions while supporting agile software delivery across the full development lifecycle.

Design and develop advanced iOS applications for telephony, meetings, and collaborative productivity tools. Collaborate cross-functionally to deliver features, integrate APIs and backend services, test and debug applications, maintain code quality and automation, publish App Store releases, and stay current with Apple design guidelines and iOS technologies.

Build and scale Nuitee’s flight infrastructure from a production product into reliable API-first platform services. Responsibilities include API design, caching volatile flight offers, modeling booking data, supporting booking changes, cancellations and refunds, integrating NDC and legacy GDS flows, and improving performance and reliability. This hands-on individual contributor role requires deep backend and API expertise, flight-domain knowledge, Python experience, and ownership in a small team.

Design, build, and support MongoDB Atlas DevOps and SDK tooling, including cloud integrations, Terraform providers, CloudFormation resources, and Go SDKs. Develop integration components for partner frameworks, incrementally deliver complex projects, troubleshoot customer issues through Level 2 support, and collaborate across teams. The role also involves project ownership, roadmap contributions, knowledge sharing, and mentoring.

Develop and enhance cloud infrastructure applications for reliability, scalability, and availability. Deploy and operate cloud-native services using Kubernetes and Linux-based internet infrastructure technologies. Implement monitoring, alerting, incident response, root cause analysis, and corrective actions while ensuring security and operational compliance. Collaborate with internal teams to deliver infrastructure solutions in a large-scale, high-traffic environment.

Build and maintain ERP business management features across backend services, APIs, databases, and user interfaces. Develop reliable software, implement database models and schema changes, investigate issues, write tests, monitor releases, conduct code reviews, and communicate risks. The role requires professional software development experience and offers opportunities to grow into larger engineering responsibilities while working with technologies including Python, Django, React, PostgreSQL, AWS, and Kubernetes.

Lead a cross-disciplinary team of 4–5 engineers while remaining hands-on in software architecture, performance, reliability, cloud-native AWS systems, technical innovation, and production delivery. Responsibilities include line management, coaching, quality ownership, architectural direction, stakeholder alignment, emerging technology evaluation, and deliberate use of AI tools. The role requires extensive software engineering experience and expertise in enterprise SaaS, distributed systems, deployment environments, and technical leadership.

Lead hands-on development of secure, scalable AI and agentic platform capabilities. Design and integrate LLMs, AI services, workflows, knowledge bases, APIs, data pipelines, and orchestration layers. Translate architecture into production solutions, guide engineers and vendors, conduct design and code reviews, mentor team members, and ensure reliability, security, privacy, compliance, and scalability. Collaborate across product, business, data, architecture, and engineering teams to deliver reusable AI capabilities.

Leads hands-on development of AI and agentic platform capabilities, integrating LLMs, AI services, workflow engines, knowledge bases, APIs, and data pipelines. Translates architecture into secure, scalable production solutions; guides engineers and vendors; conducts design and code reviews; mentors team members; manages technical risks and trade-offs; and partners across product, business, data, architecture, and engineering teams to deliver reusable AI capabilities aligned with security, privacy, reliability, compliance, and scale requirements.

Leads hands-on development of scalable AI and agentic platform capabilities. Designs and delivers services, integrations, workflows, APIs, data pipelines, knowledge-base enhancements, and orchestration layers. Provides technical direction, reviews designs and code, mentors engineers, coordinates vendors, and ensures production solutions meet security, privacy, reliability, compliance, and scalability standards. Partners across product, business, architecture, data, and engineering teams to implement LLM-powered solutions and modernize existing components.

Leads hands-on development of secure, scalable AI and agentic platform capabilities. Designs and delivers reusable services, APIs, workflows, integrations, data pipelines, knowledge-base functionality, and orchestration layers using LLMs and modern AI tooling. Provides technical direction, reviews code, mentors engineers and vendors, supports architecture migration, and partners across product, business, data, and engineering teams. Ensures production readiness, security, privacy, compliance, reliability, scalability, and responsible AI practices.

Leads hands-on development of AI and agentic systems for Mastercard’s consulting-focused AI platform. Designs and delivers reusable services, integrations, APIs, workflows, data pipelines, knowledge-base capabilities, and orchestration layers. Provides technical direction, reviews code, mentors engineers, coordinates vendors, and ensures secure, scalable, reliable production solutions. Partners across product, business, architecture, data, and engineering teams to implement LLM, retrieval-augmented generation, and agent workflows while supporting migration, governance, FinOps, and responsible AI practices.

Leads hands-on development of AI and agentic systems for Mastercard’s consulting-focused AI platform. Designs and delivers scalable services, APIs, workflows, integrations, data pipelines, knowledge-base capabilities, and reusable AI patterns. Provides technical direction, reviews code, mentors engineers and vendors, supports migrations, and ensures production solutions meet security, privacy, reliability, compliance, and scalability standards. Partners across product, business, architecture, data, and engineering teams to deliver applied AI capabilities.

Leads hands-on development of AI and agentic systems, reusable platform services, integrations, workflows, data pipelines, and developer capabilities. Translates architecture and product priorities into secure, scalable production solutions; guides engineers and vendors; reviews designs and code; supports migrations; and partners across product, business, data, architecture, and engineering teams. The role also advances LLM, orchestration, knowledge-base, FinOps, TokenOps, governance, reliability, and responsible AI practices.

Leads hands-on development of AI and agentic systems for a scalable enterprise AI platform. Designs and delivers reusable services, integrations, workflows, APIs, data pipelines, knowledge-base capabilities, and orchestration layers. Provides technical direction, reviews code, mentors engineers and vendors, and partners across product, business, architecture, and engineering teams. Ensures production solutions meet security, privacy, compliance, reliability, scalability, and cost objectives.

Leads hands-on development of AI and agentic systems, including LLM integrations, reusable platform services, APIs, workflows, data pipelines, knowledge bases, and orchestration capabilities. Translates architecture into production-ready solutions, mentors engineers and vendors, conducts design and code reviews, manages technical risks, and ensures security, privacy, reliability, scalability, and compliance across distributed AI platforms.

Leads hands-on development of AI and agentic platform capabilities, including LLM integrations, orchestration, knowledge bases, workflows, APIs, data pipelines, and reusable services. Translates architecture and product priorities into secure, scalable production solutions; guides engineers and vendors through design, code reviews, delivery, and mentoring. Partners across product, business, data, and engineering teams while ensuring reliability, privacy, security, compliance, and responsible AI practices.

Leads hands-on development of AI and agentic platform capabilities, including LLM integrations, orchestration layers, APIs, workflows, data pipelines, and knowledge-base features. Translates architecture into scalable production solutions, guides engineers and vendors, reviews code, mentors team members, and ensures security, privacy, reliability, compliance, and operational standards. Partners across product, business, data, and engineering teams to deliver reusable AI capabilities and support transformation initiatives.