Top Software Engineer Jobs in Dublin

Designs and executes functional, integration, API, automated, exploratory, and end-to-end tests for personalization, recommendation, experimentation, and consumer intelligence capabilities. Builds test suites, validates AI-driven outputs and consumer journeys, manages test data, performs cross-browser testing, partners with engineering and product teams, and improves automation coverage, regression efficiency, and defect detection.

Lead the architecture and technical roadmap for Stripe Tax, driving complex multi-team initiatives from exploration through production. Design scalable, resilient systems and data models for global tax compliance, emphasizing correctness, auditability, security, availability, and interoperability. Partner with engineering, product, legal, operations, and business leaders to translate evolving tax requirements into platform capabilities. Provide hands-on technical leadership, make strategic decisions, improve operational excellence, and mentor engineers.

Design, develop, and maintain high-performance consumer-facing web applications using React, TypeScript, and JavaScript. Lead frontend architecture, performance optimization, accessibility, reusable component development, API integration, experimentation, production troubleshooting, and CI/CD support. Collaborate with Product, Design, QA, Platform, and Architecture teams while mentoring engineers, conducting code reviews, supporting Agile delivery, and improving engineering quality and operational excellence.

Design, develop, and maintain high-quality web applications using CodeIgniter and PHP. Collaborate with cross-functional teams to define and ship features, ensure application performance and quality, identify and fix bugs, and maintain code quality and automation.

Software Engineer role at Paddle, a global Merchant of Record and payments infrastructure company. The posting provides limited role-specific responsibilities or qualifications, but the position focuses on software engineering using Go. Paddle offers remote or hub-based work, professional development support, unlimited holidays, and inclusive workplace benefits.

Builds software solutions for end users as a general full-stack engineer. The role emphasizes collaboration, ownership, accountability, fast-paced execution, adaptability, multitasking, rapid learning, and an ambitious, outcome-driven approach.

Build BLP’s core software across infrastructure, backend, machine learning, and product extension platforms. Responsibilities include operating secure and observable cloud infrastructure, developing performant distributed systems, applying AI to business problems, and enabling customer process automation. The role emphasizes formal reasoning, correctness by construction, maintainable systems, type systems, and functional programming. Work is available onsite in Zurich or remotely within Europe.

Build and operate production AI infrastructure powering intelligent agents at scale. Develop high-performance Rust services for model inference, orchestration, and execution; design scalable distributed systems; establish MLOps, observability, guardrails, and failure recovery; and optimize latency, throughput, reliability, and cost. Partner with agent systems and infrastructure teams to turn prototypes into hardened services serving millions of users.

Build and operate highly available analytics platform services handling large-scale event streams and terabytes of data. Design streaming ingestion, storage, search, aggregation, and distributed systems using Java, Spring, AWS, and Kafka. Deploy and automate cloud infrastructure, improve reliability and performance, troubleshoot production incidents, and collaborate with engineering, product, and data teams. Contribute through code reviews, mentoring, testing, observability, and automation.

Design, build, and maintain high-performance Android solutions for Toast POS, ship end-to-end features, collaborate with UX/PM/QA, integrate backend services, and iterate using AI-assisted tools to improve guest engagement in restaurants.

Lead the architecture, development, and productionization of AI-powered products, intelligent agents, and cloud-native analytics platforms. Design agentic systems with reasoning, memory, retrieval, evaluation, safety, and human oversight. Build scalable services and APIs using AWS, Azure, Databricks, Spark, Python, and Java. Drive technical execution, architecture reviews, DevSecOps, testing, reliability, governance, and cost optimization while mentoring engineers and coordinating globally distributed teams.

Build and lead scalable full-stack, data-intensive applications for analytics, experimentation, and decision-making. Responsibilities include team-level system design, distributed systems and API development, Databricks and Spark data processing, AI-powered agentic products using LLMs, performance optimization, cloud-native deployment, troubleshooting, secure coding, observability, CI/CD, and mentoring engineers.

Leads architecture and hands-on development of enterprise AI products, intelligent agents, agentic workflows, analytics platforms, and cloud-native services. Designs secure, scalable systems using LLMs, retrieval, orchestration, memory, evaluation, and safety controls. Guides productionization through reliability, observability, governance, CI/CD, testing, and cost optimization. Partners across engineering, product, data, security, and operations teams; coordinates global technical execution, drives design and code reviews, establishes reusable platforms, and mentors engineers.

Lead the architecture, development, and production deployment of AI-powered products, intelligent agents, and agentic workflows. Build scalable cloud-native services, APIs, analytics platforms, and distributed systems using AWS, Azure, Databricks, Spark, Python, and Java. Establish reliability, security, governance, observability, and cost-optimization practices while coordinating global engineering teams. Drive technical decisions, reviews, CI/CD, automated testing, modernization, reusable platforms, and mentorship across the engineering organization.

Lead the architecture, development, and production deployment of AI-powered products, intelligent agents, and cloud-native analytics platforms. Build agentic workflows using LLMs, retrieval systems, orchestration, memory, evaluation, and safety controls. Develop scalable services and APIs with AWS, Azure, Databricks, Spark, Python, and Java. Drive engineering standards, CI/CD, security, observability, technical execution, architecture reviews, and mentorship across globally distributed teams.

Build and lead scalable full-stack, data-intensive applications and AI-powered products using distributed systems, cloud technologies, Databricks, Spark, and LLMs. Responsibilities include system design, API and service development, performance optimization, mentoring engineers, technical troubleshooting, secure coding, testing, observability, CI/CD, and cross-functional collaboration. The role guides team-level architecture and delivers reliable analytics-driven solutions for global customers.

Build and lead full-stack, data-intensive, analytics-driven applications for business experimentation and decision-making. Responsibilities include system design, distributed systems development, Databricks and Spark data processing, AI and LLM-powered products, performance optimization, cloud-native deployment, troubleshooting, testing, security, observability, CI/CD, and mentoring engineers.

Leads the design, development, and productionization of AI-powered products, intelligent agents, and agentic workflows. Architects scalable cloud-native platforms using LLMs, retrieval systems, orchestration frameworks, and modern data technologies. Provides hands-on software engineering, drives architecture and code reviews, coordinates global technical execution, improves reliability and developer productivity through automation and DevSecOps, and mentors engineers while ensuring security, observability, governance, and performance.

Build and lead scalable full-stack, data-intensive, analytics-driven applications for Mastercard Services. Responsibilities include system design, distributed systems, APIs, Databricks and Spark development, AI-powered products and agentic workflows, performance optimization, cloud deployment, reliability improvements, technical mentoring, code reviews, testing, security, observability, and cross-functional solution delivery.

Lead technical design and hands-on development of AI-powered products, intelligent agents, agentic workflows, scalable services, APIs, and analytics platforms. Drive architecture, productionization, security, observability, reliability, CI/CD, DevSecOps, and engineering excellence across globally distributed teams. Mentor engineers, lead technical decisions and reviews, and build reusable platforms using cloud, data, and modern AI technologies.

Designs and develops scalable full-stack, data-intensive, analytics-driven applications and AI-powered products. Responsibilities include system architecture, distributed systems, APIs, Databricks and Spark development, LLM-based agentic workflows, performance optimization, cloud-native deployment, testing, observability, troubleshooting, and mentoring engineers.

Designs and develops scalable full-stack, data-intensive, analytics-driven applications and AI-powered products. Leads system design, builds distributed services and data pipelines with Databricks and Spark, develops LLM-based agentic workflows, resolves performance and reliability issues, and mentors engineers. Collaborates cross-functionally to deliver secure, maintainable cloud-native solutions using modern software engineering, testing, observability, and CI/CD practices.

Lead the design, development, and production deployment of AI-powered products, intelligent agents, and cloud-native analytics platforms. Responsibilities include architecting agentic AI systems, building scalable services and APIs, establishing reliability and security practices, leading technical execution across global teams, conducting design and code reviews, driving CI/CD and DevSecOps, mentoring engineers, and improving platform scalability, observability, and developer productivity.

Lead the design, development, and production deployment of AI-powered products, intelligent agents, and agentic workflows. Architect scalable cloud-native systems using LLMs, retrieval, orchestration, and modern data technologies. Drive architecture reviews, engineering excellence, security, observability, CI/CD, testing, and platform modernization while coordinating distributed teams and mentoring engineers.

Lead hands-on development of scalable, cloud-native AI products, intelligent agents, and agentic workflows. Architect production AI systems with orchestration, reasoning, memory, grounding, evaluation, safety, observability, and governance. Build distributed services, APIs, analytics platforms, and developer productivity tools using AWS, Azure, Databricks, Spark, Python, and Java. Drive technical execution, architecture reviews, CI/CD, DevSecOps, engineering standards, cross-team alignment, and mentorship.