Top Software Engineer Jobs in Dublin

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.

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.

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.

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 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.

Designs and develops scalable full-stack, distributed, data-intensive, and AI-powered applications. Leads system design, builds analytics and agentic workflows using Databricks, Spark, and LLM technologies, resolves performance and reliability issues, and translates business needs into secure technical solutions. The role also involves mentoring engineers, conducting design and code reviews, improving CI/CD and observability, supporting cloud-native production systems, and collaborating across teams.

Lead the design, development, and production deployment of AI-powered products, intelligent agents, and cloud-native analytics platforms. Architect agentic systems with reasoning, memory, retrieval, evaluation, safety, and human-in-the-loop controls. Build scalable services, APIs, and data applications using AWS, Azure, Databricks, Spark, Python, and Java. Drive architecture reviews, engineering excellence, CI/CD, DevSecOps, technical execution, modernization, and mentorship across globally distributed teams.

Lead the architecture and development of scalable, cloud-native AI products, intelligent agents, agentic workflows, and analytics platforms. Design production-grade systems using LLMs, retrieval, orchestration, memory, evaluation, and safety controls. Build APIs and distributed services with Python, Java, AWS, Azure, Databricks, and Spark. Drive technical execution, architecture reviews, DevSecOps, automation, reliability, governance, and mentoring across globally distributed engineering teams.

Build and lead scalable full-stack, data-intensive applications and AI-powered products. Responsibilities include system design, distributed services, APIs, Databricks and Spark development, LLM agentic workflows, performance optimization, cloud deployment, troubleshooting, testing, observability, secure coding, and mentoring engineers.

Build and lead scalable full-stack, data-intensive applications and AI-powered products. Responsibilities include system design, distributed systems, microservices, APIs, Databricks and Spark development, LLM-based agentic workflows, performance optimization, cloud deployment, testing, observability, troubleshooting, and mentoring engineers. The role translates business needs into secure, maintainable technical solutions and drives engineering quality, reliability, and production readiness.

Designs and develops scalable full-stack, distributed, data-intensive applications and AI-powered products. Leads system design, API and data architecture, performance optimization, cloud deployments, testing, observability, and production support. Collaborates with cross-functional teams to translate business needs into secure technical solutions, troubleshoots complex platform issues, and mentors junior and mid-level engineers. The role includes developing Databricks and Spark applications, LLM-based agents, retrieval systems, and agentic workflows.

Build and lead scalable full-stack, data-intensive applications using distributed systems, cloud technologies, Databricks, Spark, and AI agentic workflows. Responsibilities include system design, API and data architecture, performance optimization, troubleshooting, secure coding, testing, observability, CI/CD, production readiness, cross-functional collaboration, and mentoring engineers.

Build and operate foundational, security-critical platforms and cloud-native systems at scale. Automate infrastructure, reduce operational toil, define SLIs and SLOs, improve observability and incident response, perform capacity and performance analysis, and develop preventative reliability solutions. Participate in on-call rotations, post-incident reviews, technical design, and mentoring while collaborating with product, platform, and security engineering teams.

Develop and maintain backend database infrastructure powering Squarespace’s platform. Build automation and tooling in GCP, improve performance and scalability across MongoDB, CockroachDB, and Kafka, and design and provision infrastructure for new product capabilities. Collaborate across engineering teams, lead complex technical projects, participate in design reviews, influence architecture, and mentor junior engineers.

Build and operate cloud-native reliability, release, and test platforms. Develop automated quality gates, CI/CD integrations, test frameworks, observability, deployment verification, and developer self-service environments. Lead Kubernetes platform evolution, progressive delivery, chaos engineering, resilience validation, and reliability automation. Partner with engineering teams on architecture, standards, and automation-first practices while resolving infrastructure, systems, and networking issues.

Build and scale Toast’s labor cost and timekeeping platforms, processing tens of millions of shift events weekly. Responsibilities include designing, implementing, testing, deploying, operating, and improving backend systems; owning production services; partnering with product and design; conducting code reviews; and mentoring engineers. The role focuses on reliable, maintainable, data-intensive systems operating at massive scale.

Design, build, and operate traffic management and routing systems for eBay’s large-scale commerce platforms. Develop high-performance services using Java, C++, or Go; deploy and troubleshoot Kubernetes workloads; improve security, latency, throughput, and reliability; and use observability tools for production diagnosis. Collaborate with SRE, platform, and application teams on distributed systems and networking solutions.

Leads modernization of large-scale fraud rules and engine platforms, including migrations, scalable microservices, and high-throughput, low-latency systems. Provides technical leadership across architecture, security, compliance, project planning, and software delivery. Develops in Java, Python, and Go; mentors engineers; drives engineering excellence; and applies automation, performance tuning, resilient design, databases, and AI technologies such as generative AI and LLMs.

Lead modernization of large-scale fraud rules and engine platforms, driving migrations, architecture, secure software development, and scalable distributed systems. Lead early-stage projects, scope and estimate work, mentor engineers, and ensure alignment with architectural standards, infrastructure, security, and business needs. Develop high-quality code in Java, Python, and Go while promoting engineering excellence, automation, performance, reliability, and continuous improvement across global, high-throughput platforms.