Top Tech Jobs & Startup Jobs in Belfast

Own the strategy and roadmap for Elastic’s Streams telemetry pipeline, including data collection, ingestion, processing, routing, and integrations. Lead a distributed product management team, define adoption KPIs, collaborate across Observability, Security, and Search, and improve self-service data ingestion. Partner with customers, engineers, designers, sales, marketing, and the community to prioritize and deliver platform capabilities, messaging, and measurable product outcomes.

Lead competitive benchmarking for Elasticsearch across search, vector retrieval, analytical, and observability workloads. Build automated benchmark harnesses, datasets, query sets, and reproducible test environments; design fair system comparisons; analyze latency, throughput, resource use, cost, and retrieval quality; investigate performance differences; and collaborate with engineering and product teams to drive improvements. Publish clear technical reports and reproducible benchmark artifacts.

Lead the strategy, vision, and multi-quarter roadmap for Elastic’s vector database, embedding and reranking capabilities, hybrid retrieval, and AI search use cases. Conduct market and competitive research, define product metrics, prioritize features, and partner with engineering, cloud, and applied research teams. Guide technical trade-offs involving recall, latency, index size, ingestion throughput, model lifecycle, retrieval quality, and total cost of ownership across serverless and self-managed deployments.

Lead the vision, strategy, roadmap, and execution for Elastic Agent Builder, a context layer for AI agents. Partner with enterprise customers, sales, solution architects, engineering, data science, design, hyperscalers, and developers to define context engineering capabilities, agent benchmarking, evaluation strategies, and user experiences. Analyze the AI agent market, prioritize customer needs, evangelize the product through content and open-source projects, and drive adoption across a global ecosystem.

Develop and lead full-stack user interface work for Elastic Fleet and Streams using TypeScript, React, and Node.js. Own complex projects end to end, make architecture and system-design decisions, establish coding standards, conduct code reviews, improve testing and deployment, and collaborate asynchronously with designers, product managers, and distributed engineering teams. Build scalable interfaces for observability, log ingestion, and real-time data workflows while mentoring teammates and promoting secure, maintainable software.

Owns the technical vision and roadmap for organization-wide CI/CD and release infrastructure. Identifies and remediates performance bottlenecks and supply-chain security risks, designs scalable release gates, directs engineers through complex multi-quarter projects, and leads incident response. The role requires hands-on debugging across the pipeline stack, cross-organizational influence, technical communication, mentorship, code and design reviews, and setting engineering standards.

Develop and maintain Elasticsearch’s Inference API and plugin framework, integrating internal and external AI providers. Responsibilities include API and protocol design, streaming, asynchronous execution, rate limiting, configuration, billing integration, error handling, open-source contribution reviews, incident response, and comprehensive unit, REST, and rolling-upgrade testing. The role requires advanced Java expertise, concurrency and parallelism knowledge, API design skills, cross-functional collaboration, and autonomous work in a distributed team.

Develop core infrastructure and horizontally scalable APIs for Elasticsearch. Resolve complex performance and concurrency issues, improve cloud operations and observability, automate developer workflows, and support operational investigations. Lead cross-team projects, collaborate with open-source communities, and own technical designs and implementations from inception through delivery. Apply strong Java expertise, CI/CD practices, AI-assisted development, and distributed-team communication.

Own the production improvement loop for an AI Context Engine, improving agent behavior, retrieval, memory, telemetry, evaluation, and safe rollout. Build production services in TypeScript or Python, design observability and evaluation systems, analyze agent traces and customer feedback, and partner with data scientists, backend engineers, product, and UX. Mentor engineers, review designs, and shape the technical roadmap for agentic products with public APIs and evolving data models.

Lead the technical vision and development of Elasticsearch’s core search infrastructure, including indexing, retrieval, query execution, and relevance. Research search algorithms and data structures, contribute to Lucene, guide technical roadmaps, collaborate across teams, mentor senior engineers, and build high-performance distributed search systems. Serve as a subject-matter expert while driving projects from concept through completion.