Top AI Jobs in Belfast

Develop R automation and AI solutions supporting pharmaceutical clinical trials. Interpret requirements, identify workflow improvements, build proof-of-concept tools using R, Shiny, and LLM-supported coding, and mature successful prototypes into validated, documented, reusable solutions. Collaborate with statisticians, programmers, data scientists, and automation leads while ensuring compliance with clinical development standards, including testing, traceability, audit trails, version control, and regulated delivery expectations.

Design, implement, review, and validate production-grade Rust backend systems for AI training projects. Responsibilities include API development, persistence, asynchronous and concurrent processing, performance optimization, reliability testing, debugging, architecture assessment, and creating reproducible workspaces and containerized test environments. The role requires clear technical documentation, evaluation of edge cases and failure scenarios, and consistent delivery of approximately 15 hours of weekly project work.

Design and deliver enterprise-grade machine learning systems and AI-powered applications for banking. Build scalable, secure, distributed applications and automated cloud, desktop, and ML pipelines. Apply MLOps practices for versioning, reproducibility, and observability while collaborating with cloud and site reliability engineering teams. Develop reusable libraries and business-critical, data-intensive solutions, aligning machine learning problems with business objectives. The role may include mentoring or people leadership.

Lead AI controls enablement by translating AI risks into practical controls, partnering with Controls, Business, and Technology to design scalable solutions, perform risk reviews, implement controls, and advise senior stakeholders to ensure compliant AI adoption.

Designs and delivers AI-native solutions across business functions including People, Legal, Finance, and Operations. Responsibilities include identifying transformation opportunities, building and deploying AI agents and automated workflows, integrating enterprise systems, driving adoption, measuring business impact, applying governance and human oversight, and mentoring colleagues. The role partners with functional leaders to redesign operating models and continuously improve production AI solutions.

Build production-ready agentic AI capabilities focused on monitoring, guardrails, evaluation, security, quality, and human-agent collaboration. Perform exploratory data analysis, feature engineering, and model fine-tuning; translate research into scalable software; prototype rapidly; and ship reliable code. The role requires strong AI/ML and software engineering expertise, Python skills, cross-functional collaboration, and interest in AI security, agent orchestration, red teaming, and secure model deployment.

Lead a small team developing secure, reliable agentic AI capabilities. Responsibilities include setting technical direction, building agent monitoring, evaluation, and guardrail frameworks, performing machine learning tasks, translating research into production features, mentoring engineers, and contributing hands-on code and technical designs. The role focuses on agent collaboration, trust, security, quality measurement, and scalable software delivery.

Designs and deploys enterprise AI solutions using Claude, LLMs, RAG, agentic workflows, and ServiceNow integrations. The role combines full-stack engineering, systems integration, customer-facing solution delivery, prototyping, evaluation, security, responsible AI, and production support. The engineer collaborates with technical and business stakeholders, translates requirements into scalable AI architectures, troubleshoots deployed systems, and contributes reusable components and accelerators to NewRocket’s AI platforms.

Build and deploy enterprise AI solutions using Claude, RAG, agentic workflows, tool use, structured outputs, and workflow automation. Integrate ServiceNow with enterprise systems, develop full-stack components and APIs, evaluate AI quality, implement responsible AI controls, troubleshoot production deployments, and collaborate directly with customers. The role also contributes reusable accelerators, platforms, documentation, and delivery patterns while supporting workshops, prototypes, pilots, and production rollouts.

Architects and delivers enterprise AI, machine learning, generative AI, RAG, and agentic solutions. Designs Claude-powered applications, data and ML pipelines, cloud integrations, ServiceNow workflows, APIs, governance controls, evaluation frameworks, and human-in-the-loop safeguards. Leads technical discovery, architecture workshops, proofs of concept, client demonstrations, and production deployments while collaborating with stakeholders, engineers, consultants, and data teams.

Build and deploy enterprise AI solutions using Claude, RAG, agentic workflows, tool use, and workflow automation. Integrate ServiceNow, APIs, data platforms, and enterprise systems while ensuring security, evaluation, observability, and responsible AI controls. Work directly with customers on discovery, prototyping, implementation, troubleshooting, and production rollout. Contribute reusable AI accelerators, platform capabilities, prompt assets, and deployment patterns while collaborating with consultants, product teams, and AI engineers.

Leads AI technical direction for HotDocs, architecting and delivering production AI features, LLM and agent orchestration, RAG, evaluation, governance, and AI-enabled development workflows. Builds hands-on solutions with .NET Core and React, enhances CI/CD and AI observability, ensures security and scalability, and mentors engineers while influencing product and architecture decisions.

Provides senior application security architecture leadership with emphasis on API, AI, and agentic systems. Guides secure architecture decisions, threat modeling, secure design reviews, governance, authentication, authorization, cryptography, and cloud-native security. Partners hands-on with engineering teams, assesses existing implementations using security tooling and gateways, establishes policies and standards, mentors developers, and reports security metrics to leadership.

Build and own Supabase’s internal AI execution platform, including event-driven agent runtimes, durable state, human review, rollback, observability, evaluations, governance, and least-privilege tooling. Develop production agents, MCP integrations, infrastructure on Python and GCP, CI evaluation gates, operating metrics, and return-on-investment instrumentation. As the sole platform engineer, independently make architecture decisions, operate systems end to end, and ensure unsafe actions are structurally impossible.

Lead Supabase’s AI-native operating system by defining maturity models, company-wide standards, assessment processes, operating cadences, and transparency mechanisms. Manage two senior contributors focused on platform and enablement, drive adoption without direct authority, replace unnecessary meetings with automated reporting, integrate standards into onboarding, and measure whether AI agents reduce organizational coordination costs.

Owns strategy, roadmap, and execution for AI Gateway capabilities within an agentic AI platform. Defines API management, agent interoperability, model and tool connectivity, security, governance, marketplace enablement, and developer experiences. Partners with Engineering, Architecture, Security, Legal, customers, and other stakeholders to translate complex technical needs into product requirements, measurable outcomes, and release plans. Establishes metrics for adoption, reliability, performance, security, and business impact.

Lead enterprise Agentforce architecture and hands-on agentic AI engineering for European clients. Design agent workflows, configure Salesforce agents, integrate deterministic Apex and Flow logic, implement LLM orchestration, RAG, APIs, MuleSoft pipelines, security guardrails, and automated testing. Conduct technical discovery, advise enterprise stakeholders, and guide engineering teams through production deployments. This is a fractional, project-based advisory role requiring deep Salesforce architecture and advanced LLM engineering expertise.

Leads global AI-first MarTech engineering strategy, architecture, governance, compliance, and delivery. Oversees scalable digital platforms, public-facing properties, GenAI applications, R&D, proof-of-concepts, and automated compliance capabilities. Builds and mentors a global team of engineering and AI professionals, manages vendors, and partners with marketing, business, cloud, security, privacy, infrastructure, and legal stakeholders to deliver secure, high-performance digital experiences.

Embed with enterprise customers to lead AI adoption from demos and proof-of-value engagements through production. Build agentic applications, MCP servers, evaluation frameworks, and deployment configurations on Anthropic’s Claude platform. Advise engineering teams on AI-native SDLC practices, run workshops, scope engagements, and guide organizational adoption across engineering and business functions. Collaborate directly with Anthropic on customer implementations and product feedback.

Owns end-to-end AI transformation engagements for enterprise customers, from scoping and SOW development through delivery, closure, and expansion. The role manages scope, timelines, budgets, resources, executive stakeholders, and Applied AI Architect teams while driving adoption and measurable Claude usage growth. It also develops scalable delivery methodologies, templates, and processes, partners with Anthropic account teams, and travels to customer sites 10–20% of the time.

Own AI product opportunities from discovery through experimentation, development, testing, implementation, and adoption. Translate user and business needs into product requirements, priorities, milestones, and decisions. Coordinate developers, R&D colleagues, and stakeholders, manage risks and dependencies, gather feedback, and drive practical, scalable solutions. The role requires product or project management experience, AI fluency including LLMs, APIs, prompt engineering, and RAG, strong communication, prioritization, and comfort working in ambiguous, fast-moving environments.

Build and prototype AI-enabled tools, features, and workflows using Python, APIs, LLMs, RAG, vector embeddings, MCP, and agentic pipelines. Test emerging technologies, integrate AI models with data sources and services, debug experiments, and help transition successful prototypes into scalable production solutions. Collaborate with product and R&D teams while evaluating technical feasibility, performance, and user value.

As a Senior AI Engineer, you will implement advanced AI solutions, mentor teams, and ensure responsible AI practices, while driving innovation using modern technologies.

Leads client-facing Oracle technology opportunity shaping from initial commercial discussions through solution direction. Engages CIOs, CTOs, IT directors, and enterprise architects to understand business needs and develop outcome-led propositions across OCI, databases, integration, automation, low-code, security, analytics, and AI. Builds executive confidence, balances value and feasibility, supports bids and workshops, develops thought leadership, and collaborates with sales, marketing, architecture, consulting, and managed services teams.

Leads procurement transformation consulting engagements for UK, European, international, and global clients. Responsibilities include designing and implementing procurement operating models, digital Source-to-Pay processes, technology landscapes, data management, third-party risk programs, performance management, sustainability initiatives, automation, AI adoption, category strategies, spend analysis, benchmarking, business cases, cost reduction, and benefits tracking. Works with C-suite executives and procurement leadership teams to deliver business-led transformation.