Principal AI Engineer

This is a fully remote position, open to applicants in United Kingdom.

📋 Description

• Take ownership of the architecture for Grip's comprehensive data and AI infrastructure, encompassing the capturing and modeling of event data, as well as its storage, governance, and delivery to downstream users such as search, recommendations, analytics, and AI agents.

• Establish the standards for squad development and engage in the direct construction of shared infrastructure that is not owned by any single squad.

• Oversee the platform-wide data architecture, including capturing standards, data modeling, storage strategies, and serving layers utilized across the organization.

• Design and implement the data infrastructure that supports analytics, search, recommendations, and AI/agentic functionalities.

• Develop and scale data pipelines capable of managing high-volume event interaction data across the platform, ensuring reliability and low latency for both batch and streaming processes.

• Manage the data layer that supports Grip's Agentic products, making certain that agents and MCP-based tools have access to clean, well-structured, real-time data.

• Define data contracts and standards for product squads (Engage, Manage) to adhere to, collaborating as a technical peer to Principal or Senior Engineers.

• Establish data quality, governance, and lineage standards throughout the organization, including handling of PII in compliance with GDPR.

• Lead the technical strategy for capturing and governing new data categories (e.g., smart badge telemetry, location/proximity signals) in a lawful and privacy-compliant manner.

• Integrate observability into data systems through structured logging, freshness and quality monitoring, SLOs, and pipeline health dashboards.

• Advocate for high-quality technical communication, including proposals, specifications, and documentation that serve as a foundation for other teams.

• Mentor engineers across the organization on best practices related to data architecture and AI infrastructure.

⛳️ Requirements

• Demonstrated experience in owning data architecture at scale within a production SaaS environment, preferably in a platform-level rather than single-product role.

• Extensive experience with operational databases (Postgres, MongoDB/DocumentDB, MySQL) and analytical/data warehouse systems (Redshift).

• Proven ability to build and scale data pipelines (both batch and streaming) using tools such as Kinesis, SQS/SNS, and Lambda.

• Strong grasp of search and retrieval systems (Elasticsearch) and the impact of data modeling decisions on downstream relevance and ranking.

• In-depth hands-on experience with LLMs, coding assistants (Claude, GitHub Copilot), and agentic systems.

• Familiarity with Model Context Protocol (MCP), AI orchestration, or similar agentic frameworks.

• Knowledge of AI safety concepts, including prompt injection, jailbreaks, output validation, and guardrail design, as the data layer you build directly influences agentic systems.

• Experience with caching and performance optimization at scale (Redis/Elasticache).

• Strong fullstack proficiency in TypeScript/Node.js to effectively collaborate with product engineering teams, even when focusing on data and AI infrastructure.

• Proficient in DevOps practices, including AWS, Kubernetes/EKS, Terraform, and CI/CD pipelines.

• Excellent observability practices, including structured logging, metrics, distributed tracing, and SLOs (Datadog, Sentry).

• Familiarity with feature flags, canary deployments, and gradual rollout methodologies.

• Proven ability to drive data quality, governance, and compliance standards, with GDPR experience being particularly valuable due to our SmartBadge and location-tracking initiatives.

• Outstanding communication and influencing skills, as this role does not have direct authority over squad roadmaps and must lead through technical credibility and well-defined standards.

• A product-oriented mindset capable of translating ambiguous business objectives ("help us maximize our event data") into a clear, platform-wide technical roadmap.

🏝️ Benefits

• 25 vacation days annually.

• Opportunities for sabbatical leave.

• Company-sponsored training and professional development budget.

• Group life insurance and company health plan.