Top Python Jobs in Dublin

Designs, implements, and operates network security controls across AWS, GCP, and private cloud environments. Automates security monitoring and enforcement using Python, Go, Terraform, and related tools. Leads network security architecture assessments, supports WAF, firewall, DDoS, and IDS/IPS capabilities, develops security standards aligned with CIS, NIST, and FedRAMP, and mentors engineers while consulting with cross-functional teams.

Lead complex data analyses and data science projects using big data technologies. Develop systems, applications, and visual dashboards; assess system usage; improve data quality and processes; and build tools that address security threats and improve network reliability. Communicate technical findings to nontechnical audiences and guide peers through analytical methods, technologies, and system usage.

Designs, develops, and optimizes high-volume data pipelines in Databricks and Spark environments. The role integrates data from enterprise systems, collaborates with architects and data scientists, incorporates forecasting algorithms, optimizes Spark performance and cluster costs, follows Agile Scrum practices, mentors junior engineers, and maintains technical documentation.

Design, build, and operate enterprise-scale infrastructure platforms. Write and review production code, diagnose production issues, participate in on-call rotations, apply AI-assisted development, and improve scalability, reliability, security, and cost. Collaborate with stakeholders, decompose problems, measure impact, and contribute to platform-level technical decisions in a greenfield Dublin engineering hub.

Analyze complex customer and business datasets, translate findings into actionable insights, and own dashboards and automated self-service reporting. Partner with teams to define reporting needs, support forecasting, train colleagues in data use, and explore AI-enabled insights, alerts, and workflows. The role requires strong Excel or Google Sheets skills, working SQL knowledge, data visualization experience, and familiarity with AI tools. Python or R experience is beneficial but not essential.

Lead full-stack engineering for cloud-native financial technology platforms using React, Python, microservices, Kubernetes, and modern CI/CD. Responsibilities include coding, architecture, deployment, application security, observability, high availability, platform ownership, stakeholder collaboration, and mentoring engineers. The role supports investment strategy, portfolio management, and operations while establishing engineering standards across the organization.

Supports credit risk reporting, analytics, data quality, reconciliations, variance analysis, limit monitoring, regulatory change, and reporting controls. Develops automated reporting processes and dashboards using SQL, Python, Power BI, and Excel. Provides insights to senior stakeholders, investigates anomalies, manages concentration-risk reporting, oversees outsourced activities, and supports regulatory engagement and remediation.

Build and maintain SOAR playbooks, scripted solutions, and AI-powered workflows to automate detection, triage, investigation, and response. Develop PowerShell/Python scripts, integrate REST APIs and SIEM queries, validate automation, monitor performance, and collaborate with SOC/engineering teams to improve analyst efficiency.

Lead development of software tools and AI-powered solutions that identify Windows application compatibility regressions before release. Enhance an automation framework and test-authoring experience, analyze data to guide engineering decisions, and collaborate with global teams to resolve compatibility issues across devices, silicon platforms, and Windows releases.

Build and deploy agentic AI solutions in enterprise customer environments. Responsibilities include designing prompts, reasoning systems, tool calls, integrations, data pipelines, dashboards, and full-stack production deployments. The role partners with customers, sales teams, architects, and deployment strategists to deliver proofs of concept, MVPs, and measurable business outcomes. Engineers also evaluate AI outputs, troubleshoot platform gaps, share enablement, and provide product feedback. Approximately 25% travel is required.

Troubleshoot complex customer issues involving networking, APIs, voice, messaging, IoT, and AI products. Investigate logs and integrations using technical diagnostic tools, collaborate with customers, vendors, and engineering teams, document solutions, and improve self-service resources. The role also supports AI-first automation by building bots, automating workflows, and creating scripts to reduce repetitive support tasks.

Designs, develops, and delivers AI-enabled applications for large organisations, covering backend services, LLMs, multi-agent systems, machine learning infrastructure, and modern web interfaces. Responsibilities include integrating AI APIs, applying MLOps for deployment and monitoring, supporting responsible AI and regulatory compliance, documenting implementations, collaborating with multidisciplinary teams, and mentoring colleagues.

The role involves researching cybersecurity threats, vulnerability analysis, developing automated tools, and collaborating with teams to provide technical expertise and publish findings.

Lead design and deliver enterprise-grade AI solutions using LLMs, RAG, LangChain and vector search. Architect scalable, secure cloud/data systems (AWS, Cloudera, Databricks), build knowledge bases and APIs, optimize models in production, mentor engineers, and ensure data governance, security, and compliance.

Design and build security solutions for MongoDB Atlas multi-cloud infrastructure, ensuring high security standards while collaborating with engineering teams.

Lead complex cross-functional engineering programs delivering Observability features and platform capabilities. Drive execution, executive communication, process and tooling improvements, mentor junior TPMs, and partner with Product, Design, Marketing, and Analytics to maximize business value.

The Senior Applied AI/ML Scientist will build and ship LLM-powered features, drive quality in evaluation, improve retrieval systems, and lead technical discussions with a focus on AI and engineering collaboration.

Design, build, and operate LLM-powered applications and agentic AI workflows for employee platforms. Productionize models and services, implement monitoring and SLOs, create CI/CD and testing, build data/retrieval layers, ensure governance and security, and partner with product, SRE, security and data teams to integrate AI capabilities.

Evaluate AI model outputs on data science, statistics, machine learning, experimentation, and quantitative problems. Develop expert prompts, datasets, and reference solutions; identify statistical and methodological errors; and provide structured feedback to improve model performance. The role requires Python, machine learning, statistics, data analysis, experimentation, Pandas, and data modeling skills.

Supports fund risk reporting and oversight for regulated funds. Responsibilities include reviewing investment manager reports, conducting manager due diligence, analyzing portfolio risk indicators, preparing Annex IV and other regulatory reports, performing liquidity stress testing, preparing Risk Committee reporting, and presenting risk analyses to fund boards.

Develop and maintain Layer 1 networking software controlling physical connectivity components, including PHYs, transceivers, and gearboxes. Design features, automated tests, telemetry, and control interfaces using C, C++, and Python. Collaborate with customers, hardware, optics, manufacturing, testing, and support teams to troubleshoot network issues and bring new components to market. Provide technical leadership, own projects through deployment, and mentor junior engineers.

Configure and maintain IAM integrations across SaaS applications, internal systems, APIs, directories, and cloud environments. Implement and troubleshoot joiner-mover-leaver lifecycle workflows, resolve synchronization and authentication issues, administer LDAP and Ory Hydra, manage vulnerability updates, automate identity tasks with scripts, and maintain technical documentation and architectural diagrams. The role also supports zero-standing-privilege practices, secure design reviews, and identity security for human, non-human, and AI-agent identities.

Leads the application of data science, AI, machine learning, and statistical methods to clinical trial, real-world, and biomarker data. Develops analytical models, algorithms, dashboards, and data pipelines using R, Python, SQL, Bash, and Pandas. Generates evidence to support drug development decisions, regulatory discussions, and internal strategy while collaborating with stakeholders and communicating findings through presentations and technical documentation.

Leads DevOps capabilities for enterprise Analytics, Data, AI, and Machine Learning platforms. Responsibilities include AWS cloud infrastructure, Kubernetes and container platforms, CI/CD, Infrastructure as Code, observability, automation, security, compliance, cost optimization, and production reliability. The role partners with engineering, architecture, cybersecurity, and business teams while managing and developing global technical teams.

Leads and grows a software engineering team responsible for Windows application compatibility infrastructure. Sets technical strategy, roadmap, and execution priorities; ensures tools discover regressions before release; advances automation, AI-assisted testing, CI/CD, and incident response. Partners globally across Windows organizations, represents team outcomes to leadership, and develops an inclusive, high-performing engineering culture through hiring, coaching, and technical leadership.