Top Python Jobs in Glasgow

Leads agile software engineering efforts within Corporate Technology, providing technical direction, designing and developing secure production systems, reviewing code, and improving SDLC automation. Drives responsible adoption of AI-assisted engineering practices, establishes validation standards, and serves as a subject matter expert. Requires advanced programming, cloud-native development, system design, testing, operational stability, and collaboration across technical teams, contractors, and vendors.

Lead software engineer responsible for designing, developing, testing, deploying, and operating secure Java and React applications on AWS. Leads code quality, troubleshooting, vulnerability remediation, automation, resiliency, and responsible adoption of AI-assisted engineering tools. Collaborates with product, security, data, and platform teams in an Agile environment, while supporting cloud-native infrastructure and mentoring engineers on secure development practices.

Lead a software engineering team developing secure, scalable Java and React applications on AWS. Responsibilities include designing and reviewing production code, troubleshooting, improving engineering automation, adopting AI-assisted development responsibly, remediating vulnerabilities and dependency issues, and partnering with product, security, data, and platform teams. The role spans the full SDLC and emphasizes resiliency, security, testing, CI/CD, and operational stability.

Develop and operate secure, scalable Java and Spring Boot services supporting payments technology and regulatory reporting. Responsibilities include backend API development, system design, testing, deployment, production troubleshooting, resiliency engineering, observability, code reviews, CI/CD improvements, and collaboration with cross-functional engineering teams. Preferred work includes Python or PySpark data pipelines, Databricks, Airflow, Kafka, cloud services, event-driven systems, and financial-services reporting workflows.

Design, develop, test, deploy, and troubleshoot secure Python services, batch jobs, and data pipelines for payments regulatory reporting. Build scalable cloud solutions, create workflow designs, analyze data quality and pipeline performance, and improve reliability, observability, and automation. Collaborate with distributed agile teams, maintain enterprise code and libraries, apply secure software development practices, and validate AI-assisted development outputs.

Lead development of secure, scalable, multi-cloud platform provisioning services across AWS, Azure, and Google Cloud. Responsibilities include writing and reviewing production code, making architectural decisions, supporting reliable platform operations, mentoring engineers, improving SDLC practices, and applying responsible AI-assisted engineering tools. The role requires expertise in software engineering, public cloud, Terraform, distributed systems, microservices, and production platforms, with opportunities to build cross-cloud abstractions and support regulated financial services environments.

Build and maintain secure, scalable cloud provisioning platforms initially focused on Microsoft Azure, with future exposure to AWS and Google Cloud. Develop production code, review and debug peer code, support migrations, automate infrastructure management, and improve software delivery through AI-assisted development tools. Apply cloud-native architecture, Terraform, SDLC, Agile, DevOps, security, and reliability practices while contributing to platform design and engineering standards.

Configure, maintain, monitor, and optimize applications and infrastructure using site reliability engineering practices. Build automated CI/CD, infrastructure and network as code, observability, and reliability solutions. Collaborate with engineering and cross-functional teams to resolve complex issues, improve availability and scalability, and proactively manage risks using service level indicators and objectives. Apply validated enterprise-authorized AI capabilities to incident triage, troubleshooting, post-incident analysis, and toil reduction.

Lead software engineering efforts across design, development, testing, troubleshooting, and operational stability. Build secure, reliable Go-based services and support Java Spring applications, microservices, APIs, cloud-native systems, and automation. Guide architecture evaluations, AI-assisted engineering practices, code quality, testing, observability, and adoption of emerging technologies. Collaborate with vendors, startups, and internal teams while mentoring peers and fostering an inclusive engineering culture.

Build and maintain backend services and data pipelines for a source code intelligence platform. Integrate code analysis with CI/CD pipelines, pull-request checks, policy engines, and developer tools. Translate compliance requirements into automated code checks, write tests and documentation, monitor production components, debug cross-stack issues, and contribute to architecture discussions. Collaborate with control owners and engineering teams while supporting reliable, compliant developer workflows.

Build, maintain, and support scalable AWS infrastructure using Terraform, including EKS, databases, messaging, security, and monitoring services. Manage Kubernetes upgrades, production incidents, root-cause analysis, remediation, and Jenkins-based CI/CD pipelines. Improve observability with Datadog, CloudWatch, and Dynatrace, while contributing over time to Java or Kotlin Spring Boot development. Apply enterprise-approved AI tools responsibly and support reliable portfolio management systems for fixed income markets.

Leads multiple software engineering teams within corporate technology, providing technical coaching, setting delivery standards, managing stakeholders, and coordinating cross-team dependencies. Oversees end-to-end delivery of data-intensive products using Python, Spark, and Databricks. Drives responsible adoption of AI-assisted engineering and SDLC automation while ensuring secure, compliant, resilient, and high-quality software delivery in a financial services environment.

Leads software engineering for JPMorgan Payments Technology, developing secure, scalable Java and Python solutions. Owns public open-source repositories, releases, governance, licensing, CI, dependencies, and security quality. Builds SDKs, libraries, agent skills, and MCP integrations for external developers. Drives responsible AI-assisted engineering adoption, automation, testing, resiliency, and compliance. Evaluates architectures and vendors, supports payments integrations, and represents the firm through technical writing, public repositories, and conferences.

Leads platform engineering across distributed systems, shared libraries, cloud execution layers, and service contracts. Sets architecture and engineering standards, improves model execution performance, governs AI-assisted development practices, and drives CI/CD, testing, security, observability, and versioning. Mentors engineers, leads code reviews, resolves complex production incidents, coordinates cross-team changes, and translates business needs into technical roadmaps.

Leads engineering of secure cloud runtime compute products for JPMorganChase. Develops cloud-native solutions, improves cost, reliability, and performance, and collaborates with infrastructure, security, architecture, SRE, and application teams. Responsibilities include system design, application development, testing, operational stability, documentation, threat modeling, and adoption of validated AI-assisted engineering practices. Preferred experience includes AWS EKS, Kubernetes, cloud networking, network policies, permissions, and containerized runtime environments.

Design, build, operate, and maintain scalable distributed systems supporting CrowdStrike’s Intelligence pipelines. Gather requirements from analysts, develop processing and data integration systems, make autonomous architecture decisions, maintain Go and Python codebases, deploy production services, document solutions, train users, and communicate technical details effectively. The role requires independent execution in a geographically distributed team and includes opportunities to work with cloud platforms, APIs, web interfaces, malware analysis, and AI technologies.

Leads software engineering for cloud financial management products, designing, developing, testing, securing, and troubleshooting production systems. Builds cloud-native applications and data pipelines, improves operational stability through automation, and promotes responsible AI-assisted engineering practices. Reviews code, guides technical decisions, evaluates vendors and architectures, and mentors engineers while supporting agile delivery and continuous improvement.

Develop and maintain Kubernetes Operators in Go for automating cloud resources across AWS, Azure, GCP, and on-premise platforms. Design secure, scalable software solutions, troubleshoot operator and cloud-management issues, produce architecture artifacts, analyze data for system improvements, and contribute to agile engineering practices and technical communities.

Develops secure, scalable software solutions using SQL, Python, ETL, and data transformation technologies. Designs applications, produces architecture artifacts, troubleshoots systems, and maintains high-quality production code. Analyzes large datasets to identify patterns and improve application architecture and coding practices. Uses AWS, Databricks, big data technologies, agile development, CI/CD, and enterprise-approved AI-assisted engineering tools while validating outputs for correctness, security, and performance.

Lead design and development of React micro-frontends, shared UI frameworks, and scalable Python FastAPI services. Own architecture decisions for secure, resilient, observable, maintainable systems; review code; improve automation and operational stability; and guide responsible adoption of AI-assisted engineering tools. Collaborate with vendors and internal teams to evaluate architectural solutions and integrate services with AWS RDS and PostgreSQL.

Leads software design, development, testing, troubleshooting, code review, and operational stability for cloud financial management technology. Develops secure production code, promotes AI-assisted engineering practices, automates recurring remediation, evaluates vendor technologies, collaborates across teams, and mentors engineers. Requires advanced programming expertise, software development lifecycle knowledge, cloud-native experience, agile practices, application resiliency, security, and financial services IT knowledge.

Develops secure, scalable Python software and data engineering solutions within an agile team. Responsibilities include system design, production coding, testing, troubleshooting, architecture documentation, data visualization, and operational stability. Uses AI-assisted development tools responsibly, validates generated outputs, improves automation and coding practices, and identifies data-driven opportunities to enhance software architecture and quality.

Designs, develops, troubleshoots, and supports secure, scalable software and cloud infrastructure. The role leads CI/CD, Kubernetes, Docker, AWS, Terraform, Linux, database, monitoring, and automation initiatives; builds Databricks data pipelines; resolves root causes; evaluates technical solutions; and promotes AI-assisted engineering practices with secure validation, testing, and peer review.

Research and expand vehicle telemetry coverage across on- and off-highway architectures. Analyze vehicle network signals, OEM documentation, wiring diagrams, and field logs; connect to vehicle networks; capture and interpret data; and use debugging, scraping, reverse engineering, and custom scripts to validate coverage solutions. Partner with global engineering and product teams and travel to customer locations for vehicle testing.

Leads software engineering for a public cloud infrastructure platform supporting application teams. Responsibilities include designing, developing, testing, troubleshooting, reviewing, and securing production code; improving automation, scalability, and operational stability; evaluating architectures and vendors; and promoting modern engineering practices across the organization.