Top Artificial Intelligence Jobs in Glasgow

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.

Designs, develops, tests, troubleshoots, and maintains secure, scalable software solutions in an enterprise environment. The role involves creating production code, developing architecture and design artifacts, analyzing large datasets, improving system reliability, and using AI-assisted development tools responsibly. The engineer collaborates across agile teams, contributes to engineering communities, and applies technologies such as Python, Databricks, PySpark, cloud platforms, and artificial intelligence.

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.

Design, develop, and maintain secure, scalable software and data solutions on enterprise-scale finance platforms. Build production-quality Python code, Databricks/AWS data pipelines, visualizations, and audit-ready reporting. Produce architecture artifacts, troubleshoot complex issues, apply CI/CD and resiliency best practices, and responsibly integrate AI-assisted development tools and generative AI concepts to improve code quality and productivity.

Develops and maintains secure, scalable Java and React software for Wholesale Credit Risk. Responsibilities include system design, application development, testing, troubleshooting, architecture documentation, data analysis, reporting, and improving coding practices. Uses enterprise-authorized AI-assisted development tools responsibly, validates generated code, supports application resiliency and security, and contributes within an agile software development lifecycle.

Three-year graduate systems engineering programme involving engineering solution design and development, structured technical training, product work, professional development, and potential rotation across business units or external secondment. Candidates will build engineering skills while working with experienced engineers on customer-focused products in the defence, aerospace, space, and digital security sectors.

Leads the design and development of scalable Java applications and cloud-native AWS solutions. Drives CI/CD adoption, AI-assisted engineering practices, software quality, and secure development standards. Collaborates with product, architecture, and business teams to deliver enterprise platforms, conducts code reviews, establishes engineering best practices, and mentors junior engineers. The role also contributes to distributed systems, microservices, infrastructure automation, observability, and technical decision-making across a large enterprise.

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 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.

Lead the engineering function on a remote consulting mission by setting technical direction, managing and mentoring engineers, driving the roadmap, overseeing complex delivery, improving engineering practices, and partnering with product and business stakeholders. The role requires hands-on technical leadership, architectural judgment, agile expertise, and evaluation of emerging technologies including cloud, AI, and blockchain.

Lead the engineering function for a growing technology company on a renewable consulting mission. Responsibilities include setting the engineering roadmap, managing and mentoring engineers, guiding architecture and technical decisions, leading complex projects, improving engineering practices, and collaborating with product and business stakeholders. The role requires hands-on technical involvement, strong software engineering expertise, and the ability to evaluate emerging technologies including cloud, AI, and blockchain. French fluency and strong English communication skills are mandatory.

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.

Build BLP’s core software across infrastructure, backend, machine learning, and product extension platforms. Responsibilities include operating secure and observable cloud infrastructure, developing performant distributed systems, applying AI to business problems, and enabling customer process automation. The role emphasizes formal reasoning, correctness by construction, maintainable systems, type systems, and functional programming. Work is available onsite in Zurich or remotely within Europe.

Own daily operations and quality assurance for an internal AI-powered growth platform. Test releases, rule changes, edge cases, and regressions; document and verify bug fixes; monitor platform and agent activity; manage approval queues; evaluate agent output; escalate risks; and maintain test plans, QA checklists, runbooks, and release notes.

Lead technical design and delivery of AI-native email applications. Own architecture and implementation across backend, frontend, APIs, databases and cloud. Stay hands-on writing and reviewing code, debugging production, mentoring engineers, driving major initiatives, improving tooling, and ensuring reliability, security and observability while collaborating with product, design and AI teams.

Build and operate high-throughput backend services for financial crime detection across WorldRemit and Sendwave. Responsibilities include developing alerting, screening, risk-rating, and agentic AI investigation workflows; integrating third-party compliance platforms; improving observability, reliability, and auditability; collaborating with compliance teams; reviewing designs and code; and participating in on-call production support. The role requires strong Java and Spring expertise, event-driven systems experience, and familiarity with cloud and infrastructure tooling.

Own product features end-to-end, including architecture, integrations, technical specifications, deployment, testing, and production reliability. Use AI agents as the primary development tool, delegate implementation, critically review generated code, and ensure financial transaction reliability. Work independently as an individual contributor while helping evolve the company’s AI-first development process.

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.

Leads an engineering team developing secure developer tools, hardened GitHub Actions, AI agent capabilities, and microVM-based products. Owns product roadmaps, hiring, team growth, technical design, code reviews, delivery, quality, reliability, and customer feedback loops. Partners with Product to prioritize and ship iteratively in an autonomous, ambiguous environment while remaining technically hands-on.

Own the quality strategy and end-to-end testing pipeline for an AI-generated product handling real-money transactions. Build automated UI, browser, mobile, pre-merge, nightly, release, and production testing gates; integrate testing with CI/CD; evaluate external tools; and improve reliability of critical financial flows. The role partners with engineering and DevOps, uses AI coding agents daily, and drives quality initiatives as an autonomous individual contributor.

Lead the architecture and evolution of a Snowflake-based operational data platform. Design secure, governed, scalable data warehouse solutions, real-time ingestion, API integrations, AI-enabled capabilities, and natural-language querying interfaces. Define data flows, schemas, roadmaps, architectural standards, and governance while collaborating with engineering, data, business, and executive stakeholders. Troubleshoot complex platform issues, guide technical direction, and promote modern data engineering practices across enterprise systems.