Principal AI Engineer

Grip

Principal AI Engineer responsible for the data architecture and AI infrastructure for Grip's event platform. Collaborating on data standards and driving technical strategy in data management.

Posted 7/10/2026full-timeRemote • 🇬🇧 United KingdomLeadWebsite

Tech Stack

Tools & technologies

Amazon RedshiftAWSElasticSearchJavaScriptKubernetesMongoDBMySQLNode.jsPostgresRedisTerraformTypeScript

About the role

Key responsibilities & impact

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

What you’ll need

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

Comp & perks

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

ATS Keywords

✓ Tailor your resume

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

Data ArchitectureData Pipeline DevelopmentData ModellingEvent Data CaptureOperational DatabasesAnalytical SystemsSearch SystemsAI Safety FluencyFullstack LiteracyDevOps Fluency

Soft Skills

Technical CommunicationMentoringInfluencing SkillsProduct Mindset