Top Python Jobs in Dublin

Lead the design and evolution of an enterprise AI platform supporting experimentation through production. Manage and mentor AI engineers, define platform roadmaps, establish MLOps and LLMOps standards, and build services for model serving, inference, feature stores, vector databases, governance, and observability. Design secure cloud-native infrastructure using Kubernetes and infrastructure as code, ensure reliability and scalability, productionize AI solutions, and collaborate with architecture, security, data, product, and science teams.

Leads the design and evolution of an enterprise AI platform supporting experimentation through production. Manages and mentors AI engineers, defines the technical roadmap, and develops shared capabilities such as model serving, feature stores, vector databases, AI gateways, and registries. Establishes MLOps and LLMOps standards, cloud-native infrastructure, governance, security, observability, reliability, and automation practices. Partners with architecture, cloud, data, security, product, and data science teams to scale secure, resilient, and cost-effective AI adoption.

Lead the design and evolution of Mastercard’s enterprise AI platform, managing and mentoring AI engineers while defining platform roadmaps, MLOps and LLMOps standards, cloud-native infrastructure, model serving, governance, security, observability, and reliability practices. Partner with architecture, cloud, data, security, product, and data science teams to productionize AI solutions and deliver scalable, secure, reusable capabilities that accelerate enterprise AI adoption.

Lead the design and operation of Mastercard’s enterprise AI platform, including model serving, inference APIs, vector databases, feature stores, governance, observability, and self-service capabilities. Manage and mentor AI engineers while defining platform strategy and technical roadmaps. Establish MLOps and LLMOps standards, build cloud-native infrastructure, and ensure scalability, reliability, security, compliance, and cost efficiency. Partner with data scientists, security, architecture, and product teams to productionize AI and generative AI solutions across the enterprise.

Lead the design and operation of an enterprise AI platform supporting production AI and Generative AI solutions. Manage and mentor AI engineers, define platform roadmaps, build shared services such as model serving and vector databases, establish MLOps and LLMOps standards, and ensure security, governance, reliability, scalability, and cost efficiency across cloud-native infrastructure. Partner with architecture, security, data, product, and data science teams to accelerate enterprise AI adoption.

Lead the design and operation of Mastercard’s enterprise AI platform, including model serving, inference APIs, feature stores, vector databases, governance, observability, and developer self-service. Manage and mentor AI engineers, establish MLOps and LLMOps standards, drive cloud-native infrastructure and reliability, and partner with architecture, security, data, product, and data science teams to productionize scalable, secure AI and Generative AI solutions.

Lead the design and operation of Mastercard’s enterprise AI platform, including model serving, inference APIs, vector databases, MLOps, LLMOps, governance, observability, and cloud-native infrastructure. Manage and mentor AI engineers, define the technical roadmap, productionize AI and generative AI solutions, and ensure platform security, scalability, reliability, compliance, and cost efficiency across the enterprise.

Leads the design and operation of Mastercard’s enterprise AI platform, including model serving, MLOps, LLMOps, cloud-native infrastructure, governance, security, observability, and reliability. Manages and mentors AI engineers, defines the platform roadmap, partners with architecture, security, data, and product teams, and enables production deployment of AI and generative AI solutions at enterprise scale.

Lead the design and operation of an enterprise AI platform supporting production AI and Generative AI solutions. Manage and mentor AI engineers, define platform roadmaps, build shared services for model serving and orchestration, establish MLOps and LLMOps standards, and ensure scalability, reliability, security, governance, and compliance. Partner with architecture, cloud, data, security, product, and data science teams to accelerate enterprise AI adoption.

Lead the design and operation of Mastercard’s enterprise AI platform, including model serving, inference APIs, vector databases, registries, and developer tools. Manage and mentor AI engineers, define the platform roadmap, establish MLOps and LLMOps standards, and ensure secure, scalable, reliable cloud-native infrastructure. Partner with architecture, security, data, product, and science teams to productionize AI solutions while implementing governance, observability, compliance, automation, and operational excellence.

Lead the design and evolution of an enterprise AI platform supporting experimentation through production. Manage and mentor AI engineers, establish MLOps and LLMOps standards, build cloud-native services for model serving and orchestration, and ensure scalability, reliability, security, governance, and cost efficiency. Partner with architecture, cloud, data, security, product, and data science teams to productionize AI and generative AI solutions while driving platform strategy, operational excellence, and engineering best practices.

Leads end-to-end software engineering for analytics platforms and applications, including architecture, development, testing, deployment, support, and technical direction. Builds scalable AI-powered solutions and large-scale data pipelines with Python, PySpark, and SQL. Evaluates emerging AI tools, maintains GitHub Actions CI/CD, supports cloud development, conducts reviews, creates prototypes, documents systems, and partners with product, architecture, data science, and engineering teams.

Lead architecture and development of backend services, integrations, internal tools, and data systems that measure engineering health, AI and tooling spend, ROI, and costs. Build auditable APIs and reporting systems, replace manual processes, ensure quality and reliability, monitor production systems, drive projects from design through rollout, collaborate with product and business stakeholders, and mentor engineers using agent-assisted practices.

Leads data scientists, analysts, and engineers integrating pricing models into an enterprise pharmacy pricing platform. Provides technical leadership across solution design, platform integration, production delivery, analytics architecture, and software engineering. Manages resources, coaches team members, partners with product, engineering, and business leaders, drives continuous improvement, and communicates analytical results and predictive models. The role requires Python and SQL expertise, people management, enterprise production delivery, financial modeling, and Agile experience.

Design, deploy, and operate production AI agents and generative AI solutions using Azure OpenAI, Snowflake, Databricks, retrieval, semantic models, and tool orchestration. Build reliable data workflows, governance, security, monitoring, evaluation, and responsible AI controls for sensitive healthcare data. Integrate AI systems with enterprise applications and APIs, troubleshoot performance and retrieval issues, and collaborate with technical and business stakeholders to deliver compliant, scalable solutions.

Designs, builds, and maintains AI-driven marketing automations, integrations, and workflows across platforms including Workato, Marketo, Iterable, and Salesforce. Partners with marketing, analytics, IT, and engineering teams to translate campaign needs into scalable technical solutions, improve data integrity, troubleshoot integrations, and optimize processes. The role also develops documentation, supports governance and compliance, and serves as a marketing automation subject matter expert.

The role focuses on leading cross-functional technical programs, enhancing program delivery processes, and mentoring junior team members, utilizing strong engineering and communication skills to align with stakeholders.

Design, build, and operate enterprise-scale infrastructure platforms; write and review production code; own reliability, performance, security, and cost; run on-call rotations and respond to incidents; use AI-native engineering practices to accelerate development and automation; collaborate on technical decisions and decompose ambiguous problems into production-ready systems.

Lead a small senior team designing, building, and operating enterprise-scale infrastructure platforms. Own architecture through production, write and review production code, run on-call rotations, establish AI-native engineering practices, ensure security and reliability, decompose ambiguous problems, measure outcomes, and collaborate with stakeholders to drive scalable, cost-effective infrastructure solutions.

The Quant Trader will manage trading positions, analyze data for opportunities, enhance trading tools, and collaborate with teams to solve complex problems in a trading environment.

Lead Platform Engineer responsible for designing, building, automating, and operating enterprise PostgreSQL and Cassandra platforms. Duties include administration, performance tuning, HA/DR, cloud migration support, observability, Infrastructure as Code, CI/CD integration, and cross-team technical leadership to ensure scalable, reliable, and compliant database services.

Lead design, build, automate, and operate enterprise PostgreSQL and Cassandra platforms. Ensure high availability, performance tuning, backup/recovery, security, cloud migrations, observability, and platform automation while mentoring engineers and collaborating across teams.

Lead and operate enterprise PostgreSQL and Cassandra platforms: design, build, automate, monitor, and support high-availability, scalable, secure database solutions; drive cloud adoption, modernization, performance tuning, backup/recovery, and incident resolution while mentoring engineers.

Lead design, build, automate, and operate enterprise PostgreSQL and Cassandra platforms. Ensure high availability, performance tuning, backup/recovery, DR, monitoring, and cloud adoption. Provide technical leadership, collaborate with infrastructure and security teams, and drive platform modernization and automation via IaC and CI/CD.

Lead Platform Engineer responsible for designing, building, automating, and operating enterprise PostgreSQL and Cassandra platforms. Ensure high availability, performance, security, and scalability; lead migrations, cloud adoption, monitoring, and automation; provide technical leadership and cross-team collaboration.