Top Python Jobs in Dublin

Design, build, test, and deploy scalable, reliable enterprise solutions. Collaborate with architects and stakeholders to gather requirements, implement features, fix bugs, optimize distributed system performance, work in agile sprints, and mentor junior engineers.

Own remote access, edge security, OS lifecycle, provisioning, and networking posture for a global fleet of Linux edge devices. Build and operate tooling for remote management, patching, endpoint protection, cloud/edge integration, and customer security reviews. Collaborate with Edge Engineering, IT, and customer security teams; document processes and respond to field incidents to maintain secure, resilient deployments.

Design, implement, and optimize a real-time, high-performance video analytics pipeline on edge devices. Own custom GStreamer plugins, decoding, batching, inference, tracking, and edge-to-cloud delivery while ensuring low latency, reliability, and observability.

Build and maintain BigQuery data models and ETL pipelines using Dataform and Python; implement data quality and observability; schedule workflows with Cloud Composer/Airflow; support Looker reporting and ML feature pipelines; collaborate with Data Science and Product to productionize analytics.

Operate and scale an AI-security SaaS platform using SRE principles: monitor SLOs, manage incidents and on-call rotation, troubleshoot customer-facing issues, automate via IaC and scripting, collaborate with development teams to improve observability, reliability, and security-as-code.

Perform compliance evaluations for safety, EMC, mechanical, and environmental standards. Execute and document lab test plans, develop fixtures and automation tools, support certification campaigns with external labs, debug and rework assemblies, and review schematics/PCB/layouts for compliance to safety and EMC requirements.

Design, deploy, operate, and improve scalable production infrastructure with strong reliability, observability, performance, and security. Build automation, monitoring, alerting, incident response, and infrastructure-as-code solutions. Collaborate with software engineering teams to resolve infrastructure bottlenecks, manage maintenance and staged releases, troubleshoot platform issues, conduct postmortems, and maintain resilient cloud and containerized systems.

Leads development and deployment of expert and generalist robot policies for industrial automation. Designs task-planning and policy-learning systems using hierarchical planning, reinforcement learning, and hybrid methods. Develops simulation and real-world datasets, guides sensor integration, collaborates across embedded and hardware teams, and advances AI platform architecture, CI/CD, and MLOps. Provides technical leadership, establishes roadmaps, mentors engineers, and deploys robotics algorithms into real-world systems.

Build and deploy production-grade LLM capabilities for the Kayzen Console. Responsibilities include developing AI-backed APIs and full-stack features, implementing RAG, embeddings, agents, and tool calling, and establishing evaluation, monitoring, observability, and feedback systems. The role optimizes quality, latency, reliability, and cost; troubleshoots production issues; collaborates with Product, ML, and Engineering; and turns prototypes into maintainable AI products.

Customer-facing consultant who embeds with clients to understand challenges, design solutions, build prototypes and production systems, and guide deployment and adoption. The role spans Azure, AI, Microsoft 365, Power Platform, and Fabric, requiring hands-on implementation, enterprise integration, security, governance, monitoring, and operational readiness. The consultant will communicate with technical and business stakeholders, develop reusable accelerators, support pre-sales activities, and deliver measurable customer outcomes.

Provides advanced technical support to enterprise customers, troubleshooting cloud infrastructure, networking, Linux systems, containers, and security issues. Performs root cause analysis, supports deployments, maintains SLAs, documents solutions, and collaborates with engineering, product, and sales teams. The role also mentors junior staff, contributes to training resources, and helps optimize infrastructure as code, observability, identity management, databases, and customer environments.

Migrate SQL Server data products and analytical workloads to a modern cloud platform. Redesign legacy SQL, ETL processes, and business logic; build scalable pipelines and analytical models; validate data quality; collaborate with stakeholders; and improve platform reliability, performance, cost efficiency, and AI-assisted data engineering automation.

Build and evolve Ridgeline's AI data platform: design secure API integrations and MCPs, implement RAG pipelines and vector database solutions, scale distributed systems, enforce data lineage/access controls, and mentor peers while shaping AI platform strategy.

Design, build, and operate large-scale data pipelines and a Snowflake-based warehouse/lakehouse using Airflow, DBT, and Python. Integrate diverse data sources, enforce data quality SLAs, participate in on-call rotations, drive architecture and roadmap decisions, mentor engineers, and collaborate with ML/product teams to enable AI-ready data products.

Build and architect high-performance advisory brokerage services for block trading, portfolio management, and IRA products. Develop frontend and backend systems, databases, and distributed architectures with strong concurrency, scalability, availability, and low-latency performance. Design order management and financial transaction systems while contributing across the technology stack in an early-stage environment.

Design, build, and operate large-scale, low-latency telemetry pipelines and observability systems for GPU cloud and edge infrastructure. Instrument compute, storage, networking, and AI workloads; implement metrics, logging, tracing, SLOs, alerting, dashboards, anomaly detection, and integrate telemetry into operational workflows. Lead observability initiatives, collaborate with platform teams, and support on-call responsibilities.

Leads data and analytics consulting projects from planning through delivery. Responsibilities include capturing client requirements, modeling scenarios, developing data processes and models, designing solutions, building dashboards, testing and assuring implementations, supporting decision-making, leading analysts and consultants, and preparing client reports and pitch materials. The role also requires selling consulting solutions, facilitating workshops, and managing client engagements.

Own design, deployment, and operation of high-performance AI GPU fabrics and datacenter networking (RoCE, RDMA, BGP/ECMP, EVPN/VXLAN). Provide staff-level architecture, cross-team technical leadership, incident escalation, automation (Python/Bash), and operational standards for global datacenter and edge deployments, including inter-datacenter transport and security.

Hands-on engineer responsible for deploying, validating, and operating GPU cloud infrastructure in datacenters. Duties include rack-and-stack, cabling and optics validation, BIOS/firmware and GPU/DPU bring-up, network and storage integration, platform stack installation, acceptance testing, runbook creation, Day-2 maintenance, observability validation, and cross-team coordination with vendors and engineering for production readiness.

Design, build, and operate the AI storage layer for GPU-heavy edge and core deployments. Architect and optimize storage for distributed training and inference, integrate storage with Kubernetes (CSI), tune performance (RDMA, NVMe-oF, GPU Direct Storage), lead reliability and operational practices, and provide staff-level architectural ownership and cross-team influence while executing hands-on storage engineering.

As a Solutions Engineer in the Technical Success team, you will guide Digital Native customers in leveraging OpenAI's APIs to maximize business value, manage pre-sales needs, and ensure effective deployment of AI solutions across various applications.

Design, develop, and maintain Selenium-based automated test suites for backend services and APIs; integrate tests into CI/CD pipelines; validate integrations and data; log and track defects; collaborate with developers and product teams to improve test coverage and report regression status.

Design, build, and deploy production-grade agentic AI systems at enterprise scale. Lead client engineering engagements, define RAG and multi-LLM standards, own LLMOps (eval, prompt governance, observability), implement cloud-native architectures, and publish reusable patterns. Manage and develop engineering teams and measure agentic system quality across accuracy, latency, safety, and cost.

Provide technical troubleshooting and support for Sprinklr's Unified-CXM platform, investigate and resolve customer-reported issues, collaborate with engineering/product teams, maintain documentation, perform QA/testing, and meet SLAs to ensure customer satisfaction.

Provide technical support for ClickHouse and Langfuse customers across EMEA and global regions through cases, chat, Slack, community channels, and calls. Troubleshoot database, cloud infrastructure, AI application, tracing, and evaluation issues within SLA and on-call rotations. Develop documentation and educational content, assist with technical proofs of concept, mentor colleagues, escalate bugs, collaborate with Engineering and Product teams, and support customer implementations directly in codebases.