Top Python Jobs in Dublin

As a Staff Forward Deployed Engineer at Intercom, you will work with strategic customers to implement AI solutions, lead engineering functions, and mentor team members while ensuring effective communication across teams.

Support Longevity and Finsol teams and Financial Reporting by owning KPI aggregation, performance analysis, data quality improvements, stakeholder communication, and process transformation to prioritize analysis over production.

The Site Reliability Engineer III is responsible for ensuring application reliability, performance, and scalability on the Guidewire Cloud Platform, using automation and engineering skills to troubleshoot issues, develop runbooks, and optimize systems.

As a Software Engineer III, you'll collaborate with stakeholders, design complex features, mentor junior engineers, and implement best practices for software delivery.

Partner with customers to design, prototype, and deploy AI-enabled cybersecurity workflows using OpenAI models and tooling. Lead discovery, scope pilots, build demos/proofs, advise on safe implementation patterns, create reusable field assets, and provide product feedback across AppSec, cloud security, SOC/IR, vulnerability management, and related domains.

Advance analytics and ML solutions for a global pharma client: develop, implement and monitor models; build data models and BI analyses (Spotfire); liaise with stakeholders; improve provisioning and inspection-ready documentation; apply statistical methods to solve business use cases.

Design, build, and scale high-performance data pipelines and infrastructure (ingestion, transformation, storage, modeling, serving) using ClickHouse, Postgres, Python and dbt. Manage data quality, reliability, and observability at terabyte and 500M+ address scale, collaborate with researchers and product, mentor engineers, and leverage AI tools to accelerate work.

Design, deploy, automate, and maintain scalable cloud infrastructure and CI/CD pipelines. Lead cloud architecture, ensure security and compliance, mentor engineers, troubleshoot production issues, and improve operational efficiency using Docker, Kubernetes, Jenkins, Terraform/Ansible, and cloud provider services.

Lead a team of 5–10 technical support engineers to troubleshoot and resolve customer-reported issues, manage escalations, enforce SLAs, analyze support KPIs, create knowledge base documentation, improve support processes, hire and train staff, and coordinate with accounts and engineering to maintain positive customer sentiment.

The Software Engineer for Data Infrastructure & Acquisition will enhance data collection for AI model training, improve ingestion pipelines, and collaborate with AI scientists for optimal data usage.

Join the ROOST Osprey team to design, implement, test, and maintain a high-performance, real-time safety rules engine. Work includes building data/event pipelines, scaling and containerizing services, integrating with Kafka and gRPC, reviewing community contributions, maintaining code quality and security, and engaging with users and open source contributors to prioritize and deliver features.

Lead and grow ROOST's engineering team, set technical direction, drive high-quality open-source development and release practices, engage the external community as stakeholders, and contribute hands-on to code, architecture, and operational excellence.

Own and evolve the core data platform: warehouse design, dbt transformations, and production AWS pipelines. Refactor and harden API-driven data flows, ensure observability and testing, partner with backend and product teams, and contribute to data-aware backend features to deliver reliable, product-focused data.

Lead a hybrid QA team to own testing lifecycle from requirements to release. Design and run manual and automated web, mobile, and API tests, develop test frameworks, improve CI pipelines, mentor engineers, track defects, and ensure high-quality releases.

Design, build, and maintain the studio pipeline and artist-facing tools (launchers, publishers, loaders, review/notes). Create fast, responsive front-ends for web, Qt/PySide, and in-engine (Unreal). Integrate with Maya, Unreal, Nuke, and Perforce on Windows, extend the AYON pipeline, add AI-assisted features, own tools through their lifecycle, and collaborate directly with artists while managing your own work.

Build and operate secure, scalable AWS backend services for digital health. Design, implement, test, and maintain serverless APIs and integrations; improve reliability, observability, CI/CD, and incident response; mentor engineers and contribute to architectural decisions across the product lifecycle.

Serve as a subject-matter expert for Agentforce/Data Cloud, advising strategic customers on architecture, integrations, performance, and solution design. Identify capability gaps, run engagement playbooks, influence executives, build cross-functional relationships, and mentor peers while ensuring data governance, ethics, and measurable business ROI.

Own end-to-end quality validation for new features and releases on a genomics platform. Design, build, and maintain scalable automated regression suites (Playwright/Cypress/Selenium), run API/integration tests (Postman/Swagger), integrate tests into CI/CD, lead exploratory testing and release readiness, track defects to resolution, improve QA processes, and mentor junior QA engineers while communicating quality risks across teams.

Lead and own platform architecture across Infrahub ecosystem, implement high-impact architectural improvements, reduce technical debt, champion AI-first engineering, provide hands-on technical leadership, mentor engineers, and collaborate with product and leadership to ensure scalable, extensible systems.

Develop and optimize large neural-network tabular models in Python. Profile training and inference pipelines, improve memory efficiency, latency, and throughput. Implement performance-critical components in Rust (and optionally C++), ensure numerical stability and reproducibility, collaborate with researchers to productionize capabilities, and maintain tests and documentation.

Build and maintain front-end and back-end systems for model interaction and large-scale inference. Develop APIs, session persistence, event-driven architectures, database integrations (Snowflake/Databricks), and monitoring/retry mechanisms. Collaborate with MLOps/DevOps to optimize deployment and ensure reliable, scalable model-serving workflows.

Build and maintain Extensions backend for enterprise LTM products: design distributed, reproducible, observable workflows; optimize latency and throughput; collaborate with data scientists; drive architectural decisions; write high-quality, tested Python code; and document best practices for production-scale deployments.

Research, develop, and productize data-science methods to improve NEXUS predictive performance on enterprise tabular datasets. Implement production-quality Python components, design experiments and benchmarks, handle real-world tabular data challenges, collaborate with Research and Engineering, and validate approaches on customer datasets to drive product features.

Design, build, and operate cloud infrastructure and Kubernetes clusters for GPU/ML workloads; implement GitOps, IaC (Terraform), CI/CD, monitoring, automation (Python/Bash), and cost-optimization alongside ML engineers.

Own and patch Chromium/Firefox C++ source to build an in-house stealth browser. Fix fingerprinting at the engine level (navigator, WebGL, canvas, fonts, Client Hints), eliminate CDP leaks, maintain per-OS fingerprint profiles, continuously rebase patches, build validation tooling, and debug detection issues to keep automation indistinguishable from real users.