Principal AI Engineer

Stack

Responsibilities

• ▹Own platform-wide data architecture: capture standards, data modelling, storage strategy and serving layers
• ▹Design and build the data infrastructure powering analytics, search, recommendations and AI features
• ▹Build and scale batch and streaming pipelines for high-volume event interaction data
• ▹Own the data layer underpinning the agentic products, giving agents and MCP-based tools clean, real-time data
• ▹Define data contracts and standards for the product squads
• ▹Establish data quality, governance and lineage standards, including GDPR-compliant PII handling
• ▹Drive the strategy for capturing new data categories (e.g. smart badge telemetry, location/proximity signals) in a privacy-compliant way
• ▹Build observability into data systems: structured logging, freshness and quality monitoring, SLOs, pipeline health dashboards
• ▹Expose well-structured data through MCP servers and tools for the Organiser and Exhibitor Agents
• ▹Mentor engineers on data architecture and AI infrastructure best practices

Requirements

• ▹Proven track record owning data architecture at scale in a production SaaS environment, ideally at platform level
• ▹Strong experience with operational databases (Postgres, MongoDB/DocumentDB, MySQL) and analytical/warehouse systems (Redshift)
• ▹Experience building and scaling batch and streaming pipelines (Kinesis, SQS/SNS, Lambda)
• ▹Strong understanding of search and retrieval systems (Elasticsearch)
• ▹Deep hands-on experience 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
• ▹Caching and performance at scale (Redis/Elasticache)
• ▹Full-stack literacy across TypeScript/Node.js
• ▹DevOps fluency: AWS, Kubernetes/EKS, Terraform, CI/CD
• ▹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)
• ▹Product mindset: translating ambiguous business goals into a platform-wide technical roadmap

Nice to have

• ▹Experience with event technology, SaaS platforms or B2B applications
• ▹Experience building data infrastructure that feeds ML models or AI agent systems
• ▹Familiarity with prompt engineering, fine-tuning or AI model optimisation
• ▹Real-time systems, WebSockets or live data pipelines
• ▹Experience with real-time location/proximity data (Bluetooth/RFID/UWB)
• ▹Prior platform/infrastructure role distinct from product engineering
• ▹Open-source contributions or a public portfolio of data engineering or AI/agentic work
• ▹Experience with security compliance frameworks (SOC 2) for AI systems

Soft skills

What we offer

• ▹Remote-first culture with an optional office in London Bridge
• ▹Competitive salary, equity and benefits
• ▹25 holiday days per year, sabbatical leave opportunities
• ▹Company training and professional development budget
• ▹Group life insurance and company health plan
• ▹Real influence over technical direction platform-wide

About the company

Grip is an AI-powered, end-to-end event platform that helps organisers build and track relationships between participants across multiple events. Its customers include event organisers such as Ascential, Hyve, Emerald and Clarion Events.