Top AI Jobs in Belfast

Owns full-cycle sales of Akamai’s cybersecurity, cloud, edge, and internet technology solutions to strategic enterprise accounts. Responsibilities include building executive-level customer relationships, identifying growth opportunities, managing sales pipelines and forecasts, achieving revenue quotas, and coordinating with cross-functional teams and partners to deliver customer requirements. Requires direct enterprise technology sales experience, strategic account management expertise, and strong understanding of security, networking, and internet technologies.

Serves as the technical authority for a GitLab product group across complex enterprise pre-sales opportunities. Leads technical discovery, architecture, workshops, demonstrations, Proof of Value evaluations, executive briefings, competitive positioning, and customer handoffs. Builds reference architectures, demo environments, playbooks, battlecards, and enablement content while mentoring Account Solutions Architects. Partners with Product, Engineering, Marketing, and post-sales teams to deliver customer feedback, adoption, and production outcomes.

Own the B2B sales pipeline and revenue for AI and data services. Responsibilities include outbound prospecting, qualifying technical buyers, managing complex pilots and recurring contracts, developing partnerships and channels, shaping pricing and commercial terms, protecting margins, and feeding customer demand into product and operations. The role requires experience selling AI/ML data, annotation, licensing, or related technical services to research and enterprise buyers.

Design, develop, and operate a scalable GenAI prompt security platform protecting AI and LLM applications from adversarial attacks and prompt injection. Build automated security testing frameworks, secure APIs, and libraries; contribute to architecture, reliability, and scaling; deploy containerized solutions; and collaborate with Engineering, Operations, SRE, and global stakeholders.

Build and deploy production-grade AI applications for Citi’s global lending platform. Implement MCP tools and AI agent frameworks, apply LLMs to business problems, integrate REST APIs and databases, write Python and SQL, participate in Scrum ceremonies and code reviews, and contribute to technical standards. The role requires independent problem-solving, collaboration, and delivery of reliable software in an enterprise financial environment.

Lead hands-on development of enterprise AI systems powering Citi’s global lending platform. Design AI applications, MCP tools, and agents using LLMs; make architecture decisions; drive features through production; ensure testing, observability, security, and operational readiness; mentor engineers; lead code reviews; and partner with product, architecture, and senior stakeholders on scalable technical solutions.

Lead NVIDIA’s engagement with AI-native startups, scaleups, and labs. Understand customer needs, develop AI technology solutions, coordinate technical and business resources, drive adoption and partner growth, create customer references and case studies, identify emerging use cases, and represent NVIDIA at industry events.

Owns strategy and growth for a defined market segment within CluePoints’ clinical-trial SaaS portfolio. Responsibilities include developing go-to-market strategies, coordinating product, marketing, sales, consulting, customer success, and finance teams, enabling teams to launch and support products, advising strategic customers, and leading user communities. Success is measured through market penetration, win rate, retention, NPS, and gross margin.

Own and build the company’s metadata-driven data layer as a hands-on principal architect. Design schema-flexible and versioned platforms with lineage, auditability, semantic mapping, and resilience to schema changes. Write production code, establish AI-assisted engineering practices with verification, coach engineers, and communicate architecture to technical and business stakeholders. Experience with regulated data, multi-tenant SaaS, semantic technologies, or clinical data standards is valuable.

Build and lead development of production-grade AI systems powering Citi’s global lending platform. Design AI software components, MCP tools, and agents using enterprise data and LLMs. Provide hands-on technical leadership, architecture guidance, code reviews, mentoring, and stakeholder collaboration while ensuring scalability, testing, observability, security, and operational readiness.

Leads the demand generation engine, translating go-to-market priorities into segmented campaigns across email, search, social, content, webinars, and events. Owns marketing automation, lead scoring, Salesforce integration, pipeline reporting, conversion metrics, budgets, and agency performance. Partners with Sales and Commercial Operations to improve handoffs and qualified opportunities, applies AI and automation to campaign execution, and recruits and coaches future demand generation team members.

Sources new sales opportunities for Premier Research, converts outreach into qualified client meetings and proposal submissions, maintains prospect and pipeline records, manages unassigned accounts, tailors outreach strategies, and presents company service information. The role requires a bachelor's degree, strong communication and analytical skills, organization, self-motivation, and 0–2 years of lead generation, inside sales, or business development experience, preferably in life sciences.

Conduct outbound cold calls and emails, identify prospect needs, qualify marketing leads, develop new business, and achieve sales targets. The representative will engage C-level stakeholders, communicate product value, collaborate across sales teams, and serve as a subject matter expert on Abnormal AI offerings. Fluency in Dutch, strong communication, organization, resilience, and experience with sales techniques are required.

Own the market strategy and growth of Luma’s lab automation and orchestration solutions. Engage pharma, biotech, CDMO, and research customers; define segments, personas, positioning, competitive strategy, pricing inputs, and AI use cases. Enable global sales and marketing teams with messaging and sales tools, align Siemens organizations, support strategic pursuits, and build partnerships with automation vendors and thought leaders. Drive software adoption, pipeline growth, and customer movement toward connected and autonomous laboratories.

Own a core AI product by translating client and business needs into validated specifications, AI-assisted prototypes, sprint-ready backlogs, user stories, acceptance criteria, and product documentation. Manage Azure DevOps backlog processes, support Agile ceremonies, incorporate user feedback, and contribute to release communications and go-to-market materials. Collaborate with product, delivery, technical, engineering, and client stakeholders while applying practical knowledge of GenAI, LLMs, RAG, agentic AI, SaaS development, and release management.

Lead and grow Nerdio’s EMEA SDR organization by hiring, coaching, and developing multilingual teams; owning pipeline targets; entering emerging markets; defining ICPs and territories; developing localized and partner-led strategies; analyzing conversion and activity data; forecasting; integrating AI into prospecting and coaching; and partnering with Sales, Marketing, Partners, and Sales Ops.

Build and operate OrderYOYO’s production data and AI platform, including Microsoft Fabric lakehouse solutions, scalable ingestion pipelines, semantic models, monitoring, data quality, and legacy-platform migrations. Develop with Python, PySpark, SQL, and T-SQL; manage performance, cost, and reliability; and collaborate with Finance, Product, executives, and engineering. Deliver applied AI and machine-learning capabilities such as RAG, agents, churn, recommendations, personalization, fraud, and risk models.

Own the AI Platform product backlog, roadmap, discovery, sprint ceremonies, requirements, prioritization, metrics, releases, and stakeholder communication. Partner with engineering, consultants, clients, and go-to-market teams to deliver a compliant enterprise AI platform. Guide trade-offs involving security, technical debt, governance, model evaluation, routing, pricing, packaging, and open-core strategy while supporting demos and pre-sales.

Apply AI and machine learning to large, disparate datasets to detect fraud and cybersecurity threats. Build analytic solutions in Databricks using Python, SQL, and R; automate reusable pipelines; investigate stakeholder concerns; identify process gaps; recommend remediation; and communicate findings to technical and executive audiences. The role also involves directing specialized analytics teams and applying large language models to accelerate analysis and development.

Build and operate production AI capabilities across enterprise platforms, including agent runtimes, RAG, model routing, tool calling, guardrails, evaluation, monitoring, and cost and latency optimization. Ship reliable, measurable, safe AI features, develop evaluation frameworks, monitor production behavior, and collaborate with backend, platform, product, security, and client teams.

Designs scalable, secure, and resilient AI solutions by translating requirements into reusable patterns and standards. Leads technical and business design decisions, drives consistency across AI initiatives, and works closely with systems, data, and integrations. The role requires end-to-end AI delivery experience, architectural discipline, practical decision-making, experimentation with AI, and strong communication skills.

Freelance AI Specialist responsible for completing and maintaining a shared business knowledge base, improving AI workflows with Claude and Gemini, creating reusable prompts, connecting AI to business tools, documenting processes, training teams, and reporting progress. The role requires careful fact-checking, strong written communication, confidentiality judgment, basic scripting or automation skills, and self-directed project execution.

Participate in a remote AI-moderated interview about digital experiences. Answer questions about digital habits, complete simple usability tasks on a computer or smartphone, and openly share feedback about tested products and interfaces. No specialized technical background is required.

Evaluate and deploy AI models on mobile devices, benchmark performance, integrate models into Android applications and services, and optimize latency, memory, power, and hardware acceleration. The role also develops hybrid local/cloud inference routing and collaborates with AI agent engineers to integrate on-device models into agent runtimes.

Define the AI phone’s hardware platform strategy, roadmap, specifications, and validation criteria. Evaluate mobile SoCs and AI capabilities, assess power, thermal, memory, connectivity, and component trade-offs, and translate product and AI requirements into hardware decisions. Collaborate with AI and product teams, ODMs, OEMs, chipset vendors, and suppliers to select platforms, determine customization needs, and support development through production.