Top Artificial Intelligence Jobs in Glasgow

Lead development of scalable Java applications and cloud-native AWS solutions. Drive CI/CD improvements, apply responsible AI-assisted engineering practices, establish secure software standards, conduct code reviews, collaborate with business and architecture teams, and mentor engineers. The role also contributes to distributed systems, microservices, infrastructure automation, observability, security, and enterprise architectural decisions.

Participate in a two-day hackathon to build tech solutions for nonprofits, collaborate on agile teams, own projects end-to-end, develop software skills through mentorship and training, and be considered for a 2027 Software Engineer Summer Internship.

Leads software engineering within an agile Corporate Technology team, designing, developing, testing, debugging, and maintaining secure, scalable Java, microservices, and React applications. Reviews code, improves software stability, promotes AI-assisted development practices, automates recurring issue remediation, and evaluates vendor and architectural solutions. Requires expertise in SDLC practices, cloud-native technologies, CI/CD, application resiliency, security, and financial-services IT systems.

Leads hands-on development of backend systems for a source code intelligence platform. Responsibilities include building distributed indexing and search infrastructure, semantic and AST analysis, AI-agent interfaces, vulnerability discovery capabilities, and SDLC automation. The role sets technical direction, mentors engineers, evaluates AI technologies such as Claude, collaborates cross-functionally, and improves engineering processes and software quality.

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.

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.

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.

Design and develop secure Java applications, React interfaces, SQL data models, and enterprise-scale risk technology for credit risk workflows. Create architecture artifacts, optimize application reliability, use AI-assisted development tools responsibly, and collaborate with product, architecture, and business teams. Participate in testing, code reviews, agile delivery, troubleshooting, and continuous improvement across complex corporate technology environments.

Lead full-stack engineer responsible for designing and delivering scalable Java and Angular microservices, defining engineering standards, mentoring engineers, driving CI/CD and automated testing, and adopting enterprise-authorized AI-assisted development practices while collaborating with UX and product stakeholders.

Lead software engineering efforts for secure, stable, and scalable financial technology solutions. Design, develop, test, troubleshoot, and review production code; improve operational stability through automation; and promote responsible AI-assisted development practices. Mentor engineers, establish standards for validating AI outputs, apply SDLC and agile methodologies, and evaluate architectural solutions from vendors and internal teams. The role requires advanced programming expertise, cloud-native experience, resiliency and security knowledge, and familiarity with financial services IT systems.

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 delivery within an agile Enterprise Technology team. Design, develop, test, troubleshoot, and maintain secure, scalable production applications; review code and improve operational stability through automation. Evaluate architectural solutions with vendors and internal teams, promote cloud-native practices, and lead responsible adoption of AI-assisted engineering tools for coding, testing, code review, and incident analysis while enforcing security and validation standards.

Conduct and publish original research in artificial intelligence, digital manufacturing, robotics, digital twins, and related engineering disciplines. Develop and deliver undergraduate, postgraduate, and continuing professional development teaching. Supervise PhD students, contribute to curriculum development, pursue research grants, engage with industry and policy partners, and support university management, enterprise, knowledge transfer, and inclusion initiatives.

Leads delivery of cloud platforms supporting large-scale transformation, including migration, modernization, and new builds. Establishes architectural principles and platform strategy with senior stakeholders, drives technology direction, and develops platform capability and team members. Advises on AI strategy, governance, and ROI while applying AI responsibly to improve delivery outcomes. Builds standards, blueprints, customer relationships, and account strategies, and contributes to organizational platform engineering, developer productivity, and emerging technology adoption.

Design, build, and maintain secure, tested, performant backend integrations connecting GitLab agents with tools such as Slack, Claude Code, and Codex. Own complex features, develop GraphQL and REST APIs, improve automated testing, troubleshoot production issues through on-call rotations, enhance observability and resiliency, and collaborate across product, frontend, backend, and AI engineering teams.

Design and deliver secure, scalable Azure data platforms for global enterprise customers. Lead architecture engagements, roadmaps, proofs of concept, pilots, and production deployments across Microsoft Fabric, Azure Databricks, databases, governance, and AI workloads. Own technical delivery, workload health, resiliency, security, capacity optimization, and adoption outcomes. Resolve technical blockers, collaborate with product and engineering teams, develop reusable implementation assets, and mentor others while enabling Azure consumption and production-scale AI scenarios.

Leads a global software and quality engineering organization responsible for enterprise data integration products across mainframe, distributed, hybrid, and cloud environments. Oversees engineering execution, software quality, modernization, customer escalations, operational readiness, innovation, and AI-enabled practices. Partners with product, architecture, and support teams while developing talent, managing performance, fostering accountability, and ensuring reliable delivery of business-critical software.

Reviews and evaluates engineering, infrastructure, and platform documents and work products for technical accuracy, completeness, clarity, consistency, and relevance. Provides structured feedback, identifies errors and gaps, compares technical approaches, and follows defined evaluation frameworks. Requires independent work, strong communication, analytical ability, and professional engineering judgment. The role is fully remote and supports varied technical evaluation projects as an independent contractor.

Develop realistic backend coding challenges, feature implementations, bug fixes, and deterministic verification systems for AI training projects. Responsibilities include designing scalable backend scenarios, evaluating code correctness and quality, incorporating automated testing, identifying edge cases and performance issues, applying secure coding principles, and refining validation logic. The role requires strong backend programming experience, debugging and optimization skills, knowledge of algorithms and data structures, and independent technical problem-solving.

Own AI cost visibility features end to end, from Go backend services and APIs processing cloud spend data to TypeScript and React interfaces. Define product direction, understand FinOps and AI economics, build scalable cloud software, and use AI throughout development. Lead design reviews, establish engineering standards, mentor peers, and ensure reliability, usability, and measurable customer impact.

Design and build GitLab Duo CLI features in TypeScript, shape AI-assisted developer experiences, improve CLI reliability, observability, and performance, collaborate across Developer Clients, and provide technical leadership and mentorship.

Build and maintain production REST APIs using Java 21 and Spring Boot while developing AI-powered portal features with Python on GCP. Responsibilities include creating MCP and agent tooling, shipping LLM-backed products, managing Kubernetes and cloud services, modernizing legacy Java systems, conducting code reviews and testing, and advancing AI-assisted development practices across the engineering team.

Leads application engineering for an AI-powered email product across backend, mobile, and desktop platforms. Designs reliable AI workflows involving orchestration, state, tool use, retries, fallbacks, and failure handling. Builds APIs connecting AI capabilities to product experiences, makes architectural trade-offs, establishes observability and operational excellence, and leads a small senior engineering team through mentorship, design reviews, and code reviews. Partners with ML leadership to deliver scalable, reliable, and maintainable production systems.

Lead application engineering for an AI-powered email product across backend, mobile, and desktop platforms. Design reliable AI workflows involving orchestration, state, tool use, retries, fallbacks, and failure handling. Build APIs connecting AI systems to product experiences, make architecture and scalability decisions, mentor senior engineers, and establish strong observability, monitoring, testing, security, and operational practices. Partner with ML leadership to ship fast, reliable, maintainable product experiences.

Build and ship native Android features in Kotlin (Jetpack Compose). Integrate backend APIs, improve performance and reliability, collaborate with product and design, use analytics, and implement AI-assisted on-device experiences where valuable.