Top Python Jobs in Dublin

Design and build Agentic AI tooling, services, and reusable patterns; implement AI-enabled applications and developer-facing capabilities; evaluate models and frameworks; improve developer experience via automation; partner across product and engineering to prototype and scale AI solutions.

Build tooling, services, and reusable patterns to apply Generative and Agentic AI across Mastercard. Design and implement AI-enabled applications, evaluate models and frameworks, improve developer experience, and deliver prototypes to production in collaboration with product and engineering stakeholders.

Build and ship Agentic AI tooling, services, and integrations that enable teams to prototype, validate, and scale AI-enabled products. Design orchestration, tool-calling, context management, and developer-facing workflows; evaluate models and frameworks for quality, cost, latency and reliability. Partner with product and engineering stakeholders to deliver reusable, production-grade patterns and improve developer experience through automation and platform thinking.

Build tooling, services, and reusable patterns to apply Generative and Agentic AI across Mastercard. Design and implement AI-enabled applications, evaluate models and frameworks, improve developer experience, and partner with stakeholders to prototype and scale production solutions.

Build tooling, services, and reusable patterns to apply Generative and Agentic AI to products and developer workflows. Design and implement AI-enabled applications, orchestrations, and integrations; evaluate models and frameworks; develop prototypes to production; improve developer experience through automation and platform thinking; partner across product, engineering, and business stakeholders.

Build tooling, services, and reusable patterns to apply Generative and Agentic AI to products and developer workflows. Design and implement AI-enabled applications, evaluate models and frameworks, develop integrations and automation, improve developer experience, and partner with stakeholders to prototype and scale AI solutions.

Lead Infrastructure Engineer designs, implements, and modernizes infrastructure for performance, resiliency, and security. Responsibilities include cloud and on-prem migrations, Kubernetes and cloud-native app administration, data streaming (Kafka/Event Grid/Service Bus), scripting and CI/CD automation, AI-assisted infrastructure analysis, and cross-functional collaboration to deliver traceable, auditable infrastructure changes.

Design, develop, and maintain secure, scalable production services. Produce architecture artifacts, implement REST APIs, operate services on AWS with containers and CI/CD, use AI-assisted dev tools responsibly, analyze data for system improvements, and ensure application resiliency and security.

Join Notion's Detection and Response team as a Security Operations Engineer, focusing on investigating security events and mentoring junior engineers, ensuring operational excellence in security practices.

Quantitative Researchers at Citadel use advanced statistical techniques to develop models and trading strategies, backtesting them in live environments.

Lead a hands-on engineering team to design and deliver IoT and edge-to-cloud solutions that integrate AI/ML for real-time workplace insights. Architect resilient, secure pipelines, enforce data governance (FAIR), drive agentic AI adoption across the SDLC, mentor engineering talent, and split time between strategic leadership and active coding.

Design, build, and maintain secure, scalable employee-facing software and AI-enabled tooling. Lead implementation of AI-assisted engineering practices, collaborate cross-functionally, apply CI/CD and cloud-native patterns (preferably AWS), and ensure resiliency, security, and validation standards across the SDLC.

Design, develop, and maintain scalable ELT data pipelines on Databricks/Palmos using Python, Spark/PySpark and SQL. Onboard enterprise datasets, apply CI/CD and testing, implement data governance and security, optimize performance, and support analytics and AI/ML use cases while leveraging enterprise AI-assisted development tools.

Lead and mentor SRE practices to design, implement, and operate reliable cloud and data platforms. Build IaC, CI/CD, observability, and containerized deployments; use enterprise AI to accelerate incident triage and reliability improvements while ensuring compliance and data sensitivity controls.

Design, implement, and modernize IoT and edge infrastructure. Architect solutions, troubleshoot moderate-complexity issues, collaborate with global teams, validate AI-assisted recommendations, manage stakeholders, and ensure resiliency, security, and operational controls.

Lead design and build production software for enterprise-scale reliability: automation, control loops, self-healing, SLI/SLO definition and alerting, observability, incident leadership, on-call ownership, toil reduction, and AI-native engineering across the SDLC while ensuring security, performance, and cost control.

Design, implement, and operate resilient cloud and data platforms. Automate infrastructure and CI/CD, instrument observability, validate AI-assisted operational outputs, manage SLO-driven reliability improvements, and collaborate across teams to troubleshoot and scale services.

Lead design and implement reliability, scalability, and observability for cloud and data platforms. Build IaC, CI/CD pipelines, use monitoring and SLO-driven improvements, apply enterprise AI for incident triage and reliability insights, and collaborate across teams to reduce toil and improve operational outcomes.

Lead reliability and observability for customer-facing digital banking services. Define SLOs/SLIs, reduce operational toil via automation and self-healing, drive performance engineering and capacity planning, set SRE standards, mentor engineers, and integrate responsible AI-assisted engineering practices to improve code quality, incident analysis, and operational outcomes.

Lead and coach data engineering teams to onboard enterprise datasets into Palmos and deliver scalable Databricks/Spark pipelines. Drive adoption of data mesh and lakehouse patterns, enforce governance, security, observability, and SDLC best practices, and enable analytics and AI/ML use cases through high-quality, reusable data products.

Lead development of secure, scalable HR/talent-management backend systems on AWS. Design, code, review, and troubleshoot production software; build IaC and data models; drive CI/CD, resiliency, automation, and responsible AI-assisted engineering adoption; lead vendor evaluations and engineering communities of practice.

Design, build, test, and maintain scalable ELT/data pipelines and architectures using Python, Databricks, and AWS. Ensure data security and controls, update data models, and perform advanced SQL and statistical data analysis to support business analytics.

The Senior DevOps Engineer will manage cloud infrastructure, implement automation tools, and mentor developers while ensuring best practices in DevOps methodologies.

The Quantitative Strategist role involves building predictive models, developing trading strategies, analyzing risks, and automating research tasks in a collaborative financial firm environment.

The role involves developing and managing distributed storage systems, ensuring reliability, and optimizing infrastructure performance. Responsibilities include defining SLOs and participating in an on-call rotation.