Top Python Jobs in Dublin

Design, implement, and support features for the MongoDB Atlas API Platform and developer tools (e.g., Atlas CLI). Build IaC tooling and integrations, work with cloud platforms, ship incremental features, investigate customer issues (Level 2 support rotation), and collaborate across distributed teams while mentoring peers.

As a Quantitative Research Analyst, you will develop and test automated trading strategies using statistical techniques and algorithms, conduct research, and analyze data.

The role involves applying advanced analytics in healthcare, developing coding solutions, collaborating with teams, and mentoring. Focus is on data science and improving healthcare outcomes.

Lead detection and response across cloud, blockchain, and AI surfaces. Build detection coverage, run incident response, deploy SOC AI tooling, maintain SIEM/SOAR and orchestration, and collaborate cross-functionally to remediate threats and improve visibility. Participate in on-call rotation and support threat modeling, vulnerability scans, and custom tooling.

Build, maintain, and improve multi-cloud and datacenter infrastructure to support threat intelligence workflows. Design and operate Kubernetes clusters, IaC, monitoring, and database systems; secure traditional and AI workloads; troubleshoot complex hardware, network, kernel, and cloud issues; document, mentor, and consult with engineering teams.

Design and build scalable, production-grade agentic AI applications and platform capabilities. Apply generative AI and agentic patterns to improve engineering productivity across the PDLC/SDLC. Collaborate with product, data science, and engineering teams to take AI-enabled solutions from prototype to production while ensuring reliability, security, and observability.

Design and build scalable, production-grade AI and agentic applications and platform capabilities. Improve engineering productivity via AI-enabled workflows, CI/CD, automated testing, and cloud-native services. Partner across product, data science, and engineering to move prototypes to reliable, secure, observable production systems.

Design and build production-grade agentic AI applications and platform capabilities. Apply generative AI patterns and AI-assisted developer tooling to improve engineering productivity, productionize AI solutions, and drive platform innovation with a focus on reliability, security, and measurable business impact.

Design and build scalable, production-grade AI and agentic applications and platforms. Apply agent orchestration, generative AI, and developer tooling to improve engineering productivity. Partner across product, data science, and engineering to deliver secure, reliable, observable, and maintainable solutions from prototype to production.

Design and build scalable, production-grade agentic AI applications and platform capabilities. Improve engineering productivity via AI-assisted workflows, CI/CD, automation, and cloud-native services while ensuring reliability, security, and measurable business impact.

Build scalable, production-grade AI and agentic applications and platform capabilities. Apply Generative AI and agent patterns to improve engineering productivity across the SDLC, productionize AI solutions with reliability, security, and observability, and partner with product, data science, and engineering teams to deliver measurable business value.

Design and build scalable, production-grade AI and agentic applications and platform capabilities. Apply AI patterns to improve engineering productivity across the product lifecycle, drive CI/CD and automation, partner with product and data science, evaluate emerging tools, and take AI-enabled solutions from prototype to secure, reliable production.

Design and build scalable, production-grade AI and agentic applications and platforms. Improve engineering productivity via AI-enabled workflows, CI/CD, automation, and developer tools. Partner with product and data science teams to take prototypes to production while ensuring reliability, security, observability, and maintainability.

Design, build, and productionize AI-enabled, agentic applications and platform capabilities. Improve engineering productivity via AI-driven workflows, CI/CD automation, and developer tooling. Collaborate with product, data science, and engineering teams to deliver secure, reliable, scalable solutions.

Design and build scalable, production-grade AI and agentic applications and platform capabilities. Apply generative AI and agentic patterns to improve engineering productivity across the SDLC. Partner with product, data science, and engineering to turn prototypes into secure, reliable, maintainable production solutions.

Design and build scalable, production-grade AI and agentic applications and platform capabilities. Improve engineering productivity via AI-assisted tooling and automation, drive AI-enabled solutions from prototype to production, and collaborate with product, data science, and engineering teams to deliver secure, reliable, and maintainable systems.

Lead Site Reliability Engineer responsible for ensuring reliability, scalability, and performance of production systems. Drive automation, observability, capacity planning, incident response, and SRE best practices. Mentor junior engineers, perform root cause analysis and post-mortems, enforce operational standards, and collaborate across development lifecycles to improve system resilience and compliance.

As a Lead Site Reliability Engineer, you will improve service lifecycles, ensure system reliability, and mentor junior team members. Responsible for incident response, system monitoring, and fostering collaboration between development and operations teams.

Lead the SRE function to ensure reliability, scalability, and performance of Mastercard applications. Implement automation, observability, incident response, capacity planning, and runbook practices. Mentor engineers, drive operational design, enforce standards, conduct post-mortems, and collaborate with developers to embed reliability throughout the lifecycle.

Lead SRE responsible for ensuring reliability, scalability, and performance of Mastercard applications. Drive production readiness, observability, automation, capacity planning, incident response, and risk/compliance. Mentor engineers, enforce operations standards, support developers in operational design, and lead proactive monitoring and continuous improvement across the application lifecycle.

Lead SRE responsible for reliability, scalability, and performance of Mastercard applications. Drives automation, observability, capacity planning, incident response, and operational standards while mentoring engineers and enforcing production readiness and risk management.

Lead SRE ensures reliability, scalability, and performance of production systems. Responsibilities include production readiness, automation, observability, incident triage and RCA, capacity planning, CI/CD and cloud infrastructure management, mentoring, and enforcing operational standards and compliance.

Lead SRE ensuring reliability, scalability, and performance of Mastercard applications. Drive automation, observability, capacity planning, incident triage/root cause, and production readiness. Mentor engineers, enforce operational standards, and align product priorities with operational risk and compliance.

Lead SRE responsible for ensuring platform reliability, scalability, and performance. Drive automation, observability, capacity planning, incident response, and SRE best practices while mentoring engineers and enforcing operational standards and compliance.

Lead Site Reliability Engineer responsible for ensuring reliability, scalability, and performance of Mastercard applications. Drive automation, observability, incident triage/root cause, capacity planning, CI/CD, cloud infrastructure, and mentor junior engineers while enforcing operational standards and risk/compliance controls.