Top Python Jobs in Dublin

Co-own and operate the analytics function: maintain and evolve dbt models, build Dagster pipelines across product, marketing and finance, run end-to-end analyses that inform decisions, co-design the analytics roadmap, and embed AI tools into workflows.

Design, build, ship, and own end-to-end product features across frontend, backend, and data. Translate ambiguous product requirements into reliable, well-tested systems; deploy, monitor, and maintain production services; participate in design and architecture, code reviews, and mentor peers while working closely with product and design teams.

Design and implement core cloud platform services, control-plane components, and internal APIs. Build platform abstractions and production-grade Go tooling, drive architectural initiatives (gRPC, eventing, cluster-api), improve scalability and developer experience, and support production incidents when needed.

Provide hands-on stabilization of multiple early-stage, often AI-generated codebases: assess, fix bugs, refactor, add missing core functionality (auth, payments), improve performance, implement lightweight testing, and collaborate across teams on fractional hourly engagements.

Platform Engineer embedding across frontend, backend, data and warehouse teams to build shared infrastructure, CI/CD, feature flags and observability. Integrate AI across the engineering lifecycle, maintain core AWS/GCP services, automate toil, coach squads on SLOs and ownership, and proactively scope and deliver high-impact platform work.

Lead product and marketing analytics to measure and improve the customer journey. Own conversion funnel and tracking, design event instrumentation (client/server-side), build dbt models and SQL datasets, analyze campaigns and CRM retention, enable self-serve analytics in Lightdash, and deliver proactive insights to Product and Marketing stakeholders.

Support merchants integrating and operating Solidgate's payments platform: analyze client requests, troubleshoot technical issues, collaborate with product and engineering, communicate with clients, and maintain product documentation. Use SQL regularly; Postman and Python experience is a plus.

Lead end-to-end cloud data platform design and delivery for omnichannel retail clients. Split time between pre-sales discovery and architectural oversight during build. Architect AI-ready data foundations (feature stores, embeddings, vector DBs), define ingestion, storage, transformation, modeling, BI and CDP integration, and enforce automation, IaC, CI/CD, testing, and observability. Co-sell and present architectures to technical and executive stakeholders.

Lead development of MATLAB/Simulink system models, control algorithms, and embedded C/C++ software for real-time systems. Build and validate digital twin solutions, integrate hardware, ROS2 nodes, sensors, actuators, and execute MIL/SIL/PIL/HIL testing. Support lab bring-up, debugging, measurements, validation, and maintain traceable technical documentation.

Design and maintain scalable data pipelines and platforms, lead migration from Snowflake to client service, propose improvements, drive initiatives, and collaborate with senior engineers, product/project managers, and data analysts.

Senior technical authority for autonomous robotic truck platforms, owning system architecture, integration, validation, and production readiness. Lead technical decision-making across hardware and software, mentor engineers, coordinate cross-functional delivery, define safety and verification strategies, address field issues, and influence long-term robotics technology roadmap.

Senior full-stack engineer responsible for designing, building, and deploying Python backend services and TypeScript front-end components. Develop scalable microservices, REST APIs, data pipelines, and UIs; integrate AI-driven document processing; ensure performance, reliability, security, and observability; write automated tests and collaborate with product, GenAI, and platform teams to deliver production-ready systems in cloud environments.

Lead QA automation for AI/LLM systems: define validation criteria for non-deterministic models, build automated and performance tests, validate RAG systems, perform API and integration testing, ensure release readiness and trace defects to data/models/requirements.

Lead DevSecOps engineer owning security and compliance implementation across infrastructure, CI/CD, Kubernetes, and cloud. Implement SOC 2/ISO controls in Drata, automate onboarding/offboarding and access reviews, drive SDLC security (SAST/SCA/secrets), run vulnerability management and incident response, and spend ~60% on infrastructure operations, monitoring, and on-call.

Lead end-to-end technical integrations of an AI voice-first CX platform into client infrastructure. Troubleshoot production issues (gRPC, SIP/VoIP, latency), deploy components with Kubernetes/Helm, coordinate with client DevOps/IT, manage releases and expectations, and drive architecture decisions for pilots.

Design and implement defensible pricing and indexing methodologies by synthesizing multiple market data sources. Build production-ready data signals, apply time-series and market microstructure analysis, and present quantitative products to institutional clients while translating technical methods for non-technical stakeholders.

Lead end-to-end physical implementation of major IP blocks or full-chip designs: floorplanning, place-and-route, clock tree synthesis, timing closure, physical verification, and automation of flows. Collaborate with RTL, DFT, verification, package, and library teams to meet PPA targets, mentor junior engineers, and drive manufacturability and sign-off across PVT corners.

Lead SRE efforts to ensure reliability, scalability, and performance of a large-scale platform. Architect observability, define SLOs/SLIs, lead incident response and post-mortems, automate infrastructure and CI/CD, optimize Kubernetes/GCP deployments, debug distributed systems, mentor engineers, and write production-quality Python or Go code.

Lead architecture and implementation of scalable, secure backend services and APIs for a global crypto payments network. Drive technical decisions, mentor engineers, collaborate with product and design, optimize performance, and champion infrastructure-as-code, DevSecOps, and security best practices across services deployed on Azure and Kubernetes.

Lead cloud infrastructure monitoring, automate operations, and design AI-driven predictive monitoring and automated incident response. Manage CI/CD pipelines, enforce cloud security/compliance, build monitoring/logging/alerting systems, perform incident triage and collaborate with development teams to optimize cloud resources.

Design, build, and maintain end-to-end test automation frameworks (UI, API, smart contracts, wallet flows), write Web3-specific tests, integrate suites into CI/CD, improve coverage, and promote quality across engineering using AI-assisted tooling.

Ensure reliability, scalability, and performance of Replit infrastructure. Build observability, automate infrastructure with IaC, establish SLOs/SLIs, lead incident response and post-mortems, optimize performance and capacity planning, and maintain CI/CD and self-healing systems.

Design, train, and deploy retrieval, reranking, and relevance ML models for a production agent-native search platform. Build embedding-based indexing and large-scale retrieval systems, define evaluation metrics and pipelines, optimize latency/quality/cost trade-offs, and collaborate with engineers to integrate models into 24x7 production services.

Build and operate services and tooling that automate network lifecycle, make network changes safe (CI/CD, rollouts, audit trails), develop scalable observability and telemetry, integrate network source-of-truth with platform APIs, and collaborate with network engineers and SREs to turn operational pain into production-grade automation.

Administer and improve the Atlassian Cloud ecosystem (Jira, Confluence, Assets, Statuspage), design workflows and automations, manage SSO/SCIM with Azure Entra ID, integrate via APIs/webhooks, ensure SaaS governance and security compliance, monitor performance, document configurations, and provide user support and training across enterprise teams.