Top Python Jobs in Dublin

Designs, builds, tests, and maintains scalable full-stack analytics applications, responsive user interfaces, data models, APIs, and data pipelines. Partners with product managers and designers to deliver customer-focused features, reviews code, improves development processes, and mentors junior engineers. The role requires strong collaboration across teams and geographies while developing solutions for credit risk, portfolio optimization, and advertising analytics.

Designs, builds, tests, and maintains scalable full-stack analytics applications, responsive user interfaces, data models, APIs, and data pipelines. Partners with product managers and designers to deliver customer-focused features, improves development processes, reviews code, ensures quality, and mentors junior engineers. The role involves Java and Spring-based backend development, React and TypeScript front-end work, distributed systems, cloud-native development, automated testing, and collaboration across teams and geographies.

Designs and builds scalable full-stack analytics applications, responsive user interfaces, data models, APIs, and data pipelines. Develops and reviews high-quality tested code, collaborates with product and design teams, mentors junior engineers, and improves development processes. The role requires strong Java and Spring Boot expertise alongside React, TypeScript, SQL, distributed systems, cloud technologies, and automated testing experience.

Designs, builds, tests, and maintains scalable full-stack analytics applications, data models, pipelines, APIs, and responsive user interfaces. Partners with product managers and designers to deliver customer-focused features, improves development processes, reviews code, mentors junior engineers, and collaborates across global teams.

Design, build, test, and maintain scalable full-stack analytics applications, responsive user interfaces, data models, APIs, and data pipelines. Collaborate with product managers, designers, customers, and global engineering teams to deliver complex features. Improve development processes, ensure code quality, mentor junior engineers, and develop innovative solutions for credit risk, portfolio optimization, and advertising analytics.

Design, build, and maintain scalable full-stack analytics applications, responsive user interfaces, data models, APIs, and data pipelines. Develop high-quality tested code, collaborate with product and design teams, mentor engineers, improve development processes, and deliver innovative solutions for financial analytics, credit risk, portfolio optimization, and marketing products.

Designs and builds scalable full-stack analytics applications, responsive user interfaces, data models, APIs, and data pipelines. Responsibilities include writing and reviewing tested code, collaborating with product and design teams, mentoring engineers, improving development processes, and delivering solutions for credit risk, portfolio optimization, and advertising analytics.

Designs, builds, tests, and maintains scalable full-stack analytics applications, responsive user interfaces, data models, pipelines, APIs, and distributed systems. Partners with product managers and designers to deliver customer-focused features, improves engineering processes, reviews code, and mentors junior engineers. The role requires collaboration across teams and geographies while supporting analytics products for credit risk, portfolio optimization, and advertising insights.

Designs, builds, tests, and maintains scalable full-stack analytics applications, responsive user interfaces, data models, APIs, and data pipelines. Collaborates with product managers, designers, customers, and global teams to deliver complex features. Ensures code quality, mentors junior engineers, improves development processes, and develops innovative solutions for credit risk, portfolio optimization, and advertising insights.

Build and deploy real-time voice and video AI models, including speech-to-speech, multimodal, and audiovisual systems. Adapt and fine-tune pretrained models, develop evaluation and data pipelines, optimize GPU inference for latency and cost, and deliver production features across backend APIs, databases, and customer portals. Own projects end to end while using coding agents and development harnesses to improve implementation, testing, debugging, and review.

Build and deploy reliable, measurable, and safe AI agents for real business workflows. Work within Marketing Engineering and growth pods to identify problems, develop end-to-end solutions, evaluate LLM performance, and measure business impact. The role involves productionizing agent systems beyond demos, using Python, SQL, LLM APIs, and orchestration tools, with potential integration into go-to-market data and marketing systems.

Supports the strategy, development, launch, scaling, and continuous improvement of AI-powered products. Translates product vision into roadmaps, manages product lifecycles, prioritizes features, tracks budgets and resources, and evaluates technical, adoption, and value metrics. The role coordinates cross-functional teams, business owners, DDIT, and external partners while ensuring stakeholder alignment, user satisfaction, ethical AI deployment, and successful transition to maintenance.

The Data Analyst III will support Fanatics Sportsbook’s Product Analytics team by delivering testing, performance tracking, reporting, ad hoc analysis, and actionable insights. The role partners with product stakeholders, analysts, and data scientists to improve user experiences and business performance. Responsibilities include presenting metrics, advising decision-makers, developing statistical analyses, and staying current with analytics and sports betting trends.

Maintain and expand Ocient’s hosted database and services platform. Responsibilities include ensuring high availability, monitoring and alerting, Linux server automation, configuration management, security practices, deployment and testing pipeline automation, backups, disaster recovery, and incident management. The role also supports cloud infrastructure, databases, networking, virtualization, and on-call operations.

Operate production Kubernetes environments and GCP infrastructure, build infrastructure as code with Pulumi, manage GitOps and CI/CD workflows, and maintain Cloudflare services. Own secrets and configuration lifecycles, observability dashboards and alerts, production incident response, infrastructure reviews, and SOC 2 security work. The role requires practical TypeScript, Python, and Go familiarity, independent execution, and core-hours overlap with the EU business day.

Leads client-facing data analytics and digital assurance engagements across infrastructure and real estate. Responsibilities include designing data-driven solutions, producing technical specifications, managing client accounts, assuring project delivery, developing teams, and driving business development, proposals, and new client relationships. The role requires expertise in analytics, business intelligence, cloud technologies, data engineering concepts, project controls, and digital solutions, along with strong communication, commercial, and people-management skills.

Leads small DFIR workstreams during incident response and recovery engagements, coordinating teams, validating technical outputs, presenting findings, and managing client expectations. Performs forensic acquisition, IOC triage, log analysis, disk and memory imaging, event correlation, timeline construction, threat research, and recovery activities. Maintains case documentation, chain of custody, compliance, and quality standards while participating in on-call rotations and traveling to client sites for deployments.

Build and scale low-latency AI serving infrastructure for SLMs, prompt-injection engines, and classification services. Architect GPU-accelerated inference pipelines, backend microservices, Kubernetes clusters, rate limiting, tenant guardrails, monitoring, and autoscaling systems. Develop continuous evaluation, retraining, model CI/CD, regression gates, and MLOps/LLMOps pipelines while improving service reliability, latency, cost efficiency, and detection quality.

Build and harden Chromium-based browser components in C++ for AI and browser security. Develop prompt-injection and Shadow AI detection, integrate AI agents, MCP servers, and CDP, and support networking and HTTP security capabilities. Build tooling and detection services with Python or Rust, deploy cloud infrastructure on AWS or GCP using Kubernetes and Terraform, and optimize high-scale systems across browser and backend environments.

Lead cloud infrastructure, systems reliability, CI/CD automation, and cybersecurity. Architect and maintain AWS/GCP environments, Docker systems, Terraform infrastructure, monitoring, disaster recovery, and deployment pipelines. Execute vulnerability scanning, hardening, compliance, incident response, secrets management, and security policy enforcement. Oversee integrations, ETL operations, infrastructure budgeting, cloud cost optimization, and account billing.

Build and optimize CI/CD pipelines, release workflows, build systems, source control, configuration management, and deployment infrastructure across multiple platforms. Manage microservice deployment lifecycles, improve reliability and security, troubleshoot infrastructure issues, and collaborate with engineering, QA, and production teams in a remote game development environment.

Designs and delivers quantum optimization solutions for customers. Responsibilities include gathering requirements, modeling business problems mathematically, developing and testing Python-based quantum hybrid applications, delivering production solutions, leading technical discussions, presenting recommendations, and collaborating with customers, delivery teams, developers, architects, tools, and product teams.

Own and improve multi-cloud production infrastructure across GCP, AWS, and Azure. Build developer platforms, CI/CD pipelines, deployment automation, Terraform modules, and production Kubernetes environments. Lead incident response, root-cause remediation, observability, networking, security, cost optimization, and reliability initiatives. The role requires hands-on automation and programming, collaboration with security and application teams, mentoring, global on-call participation, and regular overlap with U.S. Pacific Time.

Leads global AI engineering teams delivering secure, scalable AI capabilities from experimentation through production. Owns engineering strategy, architecture, portfolio planning, MLOps and LLMOps standards, production reliability, responsible AI, customer engagements, and talent development. Provides hands-on technical leadership across machine learning, generative AI, RAG, agentic systems, cloud, edge, and enterprise software while aligning delivery with customer value and business priorities.

Design and build cloud-scale directory services, authorization platforms, and policy engines. Develop scalable APIs and microservices, implement RBAC/ABAC/PBAC models, write production-ready code with CI/CD and observability, troubleshoot production issues, collaborate across Identity, Platform, Security, and Infrastructure, and adopt AI-assisted tools to automate and improve engineering productivity.