Principal AI Engineer

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🇬🇧 United Kingdom – Remote

⏰ Full Time

🔴 Lead

🤖 AI Engineer

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Grip

WebsiteLinkedInAll Job Openings

51 - 200 employees

☁️ SaaS

🤝 B2B

SaaS • B2B • Event Management

Grip is a leading AI-powered event platform designed to amplify business engagement and networking opportunities. The platform facilitates the management of in-person, virtual, and hybrid events by providing tools for event matchmaking, meeting scheduling, lead retrieval, and customized participant experiences. Grip's innovative technology helps organizers maximize event value by enhancing participant connections, increasing revenue through optimized sponsorship and exhibitor management, and ensuring smooth event operation with advanced integration and security features.

📋 Description

• Own the architecture of Grip's platform-wide data and AI infrastructure — from how event data is captured and modelled, to how it's stored, governed and served to downstream consumers including search, recommendations, analytics, and AI agents. • You'll set the standards that squads build against, and you'll directly build the shared infrastructure that no single squad owns. • Own platform-wide data architecture: capture standards, data modelling, storage strategy, and serving layers used across the organisation • Design and build the data infrastructure powering analytics, search, recommendations, and AI/agentic features • Build and scale data pipelines handling high-volume event interaction data across the platform — both batch and streaming — with reliability and low latency at the core • Own the data layer that underpins Grip's Agentic products, ensuring agents and MCP-based tools have access to clean, well-modelled, real-time data • Define data contracts and standards that product squads (Engage, Manage) build against, working as a technical peer to their Principal / Senior Engineers. • Establish data quality, governance and lineage standards across the organisation, including PII handling in line with GDPR • Drive the technical strategy for how Grip captures and governs new categories of data (e.g. smart badge telemetry, location/proximity signals) in a privacy-compliant, lawful-basis-aware way • Build observability into data systems — structured logging, freshness and quality monitoring, SLOs, and pipeline health dashboards • Champion high-quality technical communication: proposals, specifications, and documentation that other teams can build on • Mentor engineers across the organisation on data architecture and AI infrastructure best practices

🎯 Requirements

• Proven track record owning data architecture at scale in a production SaaS environment, ideally in a platform-level (not single-product) capacity • Strong experience with both operational databases (Postgres, MongoDB/DocumentDB, MySQL) and analytical/data warehouse systems (Redshift) • Experience building and scaling data pipelines (batch and streaming) using tools such as Kinesis, SQS/SNS, and Lambda • Strong understanding of search and retrieval systems (Elasticsearch) and how data modelling choices affect downstream relevance and ranking • Deep hands-on experience building with LLMs, coding assistants (Claude, GitHub Copilot), and agentic systems • Experience with Model Context Protocol (MCP), AI orchestration, or similar agentic frameworks • AI safety fluency — prompt injection, jailbreaks, output validation, guardrail design, since the data layer you build directly feeds agentic systems • Experience with caching and performance at scale (Redis/Elasticache) • Strong fullstack literacy across TypeScript/Node.js so you can work effectively with product engineering teams, even if your focus is data and AI infrastructure • DevOps fluency: AWS, Kubernetes/EKS, Terraform, CI/CD pipelines • Excellent observability practices — structured logging, metrics, distributed tracing, SLOs (Datadog, Sentry) • Feature flags, canary deployments, and gradual rollout patterns • Track record of driving data quality, governance and compliance standards (GDPR experience a strong plus given our SmartBadge and location-tracking work) • Exceptional communication and influencing skills — this role has no direct authority over squad roadmaps and must lead through technical credibility and clear standards • Product mindset — able to translate ambiguous business goals ("help us maximise our event data") into a concrete, platform-wide technical roadmap

🏖️ Benefits

• 25 holiday days per year • sabbatical leave opportunities • Company training and professional development budget • Group life insurance and company health plan