Top Python Jobs in Dublin

Lead a multidisciplinary Core Services engineering squad to design and operate distributed microservices for ledgers, balances, billing, and repayments. Translate product requirements into technical solutions, build integrations and REST APIs, enforce observability, maintain docs, improve performance and scalability, and drive CI/CD and infrastructure-as-code practices.

Lead the Core Services squad to design and implement scalable distributed microservices for ledger, billing, repayments and reconciliation. Translate product requirements into technical solutions, build integrations and REST APIs, enforce observability and CI/CD, create reusable libraries, maintain docs, and drive system performance and cross-team alignment.

Design, build, and maintain backend microservices and RESTful APIs; integrate with third-party vendors; ensure scalability, observability, and reliability; own technical architecture, CI/CD, and documentation; optimize databases and message-driven systems.

Serve as the technical pre-sales lead for DACH customers: qualify technical fit, support trials, build demos and integrations, feed product insights, and collaborate with sales and product teams to drive adoption and smooth pre-to-post-sales transitions. Must be fluent in German and work hybrid onsite.

As a Senior Finance Data Scientist, you will develop predictive financial models, analyze customer data, and communicate insights to leadership, driving strategic financial decisions.

Design, build, secure, and operate enterprise-grade APIs and hybrid integrations connecting cloud platforms to on‑prem banking systems. Deliver reusable API patterns, enforce security/compliance, implement observability and CI/CD, support production operations, and collaborate with architects, security, and business stakeholders to meet regulatory and reliability requirements.

Build and modernize Productboard’s frontend platform, migrating its legacy design system to Spark UI. Design AI-ready module boundaries, API contracts, documentation, and agent workflows involving tool use and autonomous execution. Develop high-performance React applications, validate experiments with users, collaborate with product and design teams, own features through production, mentor engineers, and share engineering knowledge across the organization.

Lead Developer Experience engineering and AI-native architecture initiatives. Build Kotlin services, Go internal tooling, developer platforms, CI/CD improvements, observability, reliability guardrails, and self-service workflows. Establish AI-ready codebase standards, context infrastructure, agent workflows, and AI code-review optimization. Partner across teams, define and measure developer-experience metrics, validate solutions with users, and promote product-minded engineering practices.

Own and build elastic.co features end-to-end across the full stack: React front-end components, backend services, CI/CD pipelines, performance instrumentation, monitoring, and security triage. Collaborate with product, design, and other engineers, perform code reviews, resolve production issues, and participate in on-call rotations for a high-availability, scalable web platform.

Design and implement quantitative trading and market-making strategies for on-chain and cross-chain markets. Build signal generation, simulation, execution, and attribution frameworks. Partner with protocol engineering to productionize research, monitor performance, and identify monetization opportunities across Defuse's intent-driven liquidity platform.

Design, build, and maintain scalable production pipelines and services to process clinical-grade 30x whole genome data. Optimize performance, reliability, and cost across AWS and hybrid environments. Develop tools and services (Python, C#, SQL, AWS) for genomic analysis, collaborate with cross-functional teams, ensure testing, observability, and validated output, and support consumer-facing DNA apps and reports.

Manage daily Data team operations, research and analyze datasets, build internal and external reports (including an annual Startup Ecosystem Ranking), and maintain/improve Python scripts and data infrastructure to deliver actionable insights.

Lead product analytics by defining metrics, building metric frameworks, analyzing funnels and user behavior, designing and analyzing A/B tests, setting up instrumentation and dashboards, and partnering with product, engineering, and leadership to turn data into product strategy and measurable business impact.

Design and analyze A/B tests, apply statistics and machine learning to improve search, ranking, personalization and recommendations, analyze large-scale behavioral data, build models and tools, and communicate findings to technical and business stakeholders to drive key business metrics.

Design and build large-scale data pipelines and models, create dashboards and tools, define and validate business metrics, ensure data quality and performance across distributed systems, and partner with analysts, engineers, and product managers to deliver actionable analytics.

Develop and scale production-grade video foundation models for human-centric video generation. Lead applied research and engineering projects involving diffusion modeling, conditioning, distributed multi-node training, evaluation, ablation studies, inference optimization, reproducibility, monitoring, and production deployment. Collaborate across teams to deliver stable, controllable, high-quality, cost-efficient video generation systems.

Develop high-quality, resilient software across Ubuntu and the open source stack, from Linux systems and firmware to cloud, containers, and desktop applications. Contribute to product roadmaps, user experience, code reviews, issue resolution, security, and enterprise requirements. Collaborate remotely with global engineering teams and the open source community, while building expertise in programming languages and Linux systems. Attend international company sprints twice yearly.

Build, deploy, and operate Cloudbeds' POS product end-to-end across React Native/Expo frontend, Python/FastAPI backend, Terraform and Kubernetes infrastructure. Implement offline-first sync, reliable APIs, payments, observability, testing, and production support while collaborating with product and cross-functional teams.

As a Senior Software Engineer, you will design and develop backend systems for healthcare AI agents, focusing on integration, performance, and reliability in clinical environments.

The AI Inference Engineer optimizes Large Language Models for inference in diverse environments, ensuring high performance and reliability through optimized deployment, hardware acceleration, and scalable architecture.

Lead AI-driven resilience assurance initiatives, utilizing predictive analytics and real-time monitoring to enhance compliance and organizational resilience. Develop autonomous systems for continuous audits and dynamic maturity assessments, translating insights into actionable strategies for stakeholders.

Lead architecture, customization, and deployment of OneTick-based time-series solutions. Design and optimize large-scale ETL pipelines, tune performance for distributed/containerized systems, and advise clients on integration strategy. Mentor engineers, drive team processes, and coordinate with product development to influence roadmap.

Design, implement and optimise Azure cloud-native solutions with Kubernetes/AKS. Manage Azure infrastructure, provision resources, develop IaC, implement CI/CD, troubleshoot performance and security, lead migrations, mentor teams, and document/runbooks.

Lead and grow an engineering team for a large-scale SaaS product. Collaborate with Product and Design to set roadmaps, design technical solutions, review code and architecture, hire and coach engineers, contribute hands-on to projects, and foster a high-performing, inclusive team culture focused on delivery and continuous improvement (especially around AI).

Design, build, and deploy reliable LLM-powered agents and agentic workflows for enterprise customers. Translate ambiguous business problems into measurable AI solutions, integrate agents with tools, APIs, and sensitive data, and ship features for Cohere’s North platform. Develop evaluation frameworks for accuracy, safety, and latency; contribute to shared AI engineering standards; collaborate with customer engineering teams; and travel 20–40% for on-site customer and partner work.