AI Platform Principal Engineer
Role Overview
Join Waters’ AI Centre of Excellence and lead the team responsible for the platform underpinning the company’s AI capabilities.
The platform provides services, tooling, and operational practices that enable development teams to build and run AI agents and solutions at scale.
This is a senior technical leadership role that remains hands-on where valuable and works across architecture, security, cloud operations, and AI engineering.
Key Skills for This Role
Full Job Posting
Role overview
Join Waters’ AI Centre of Excellence and lead the team responsible for the platform underpinning the company’s AI capabilities.
The platform provides services, tooling, and operational practices that enable development teams to build and run AI agents and solutions at scale.
This is a senior technical leadership role that remains hands-on where valuable and works across architecture, security, cloud operations, and AI engineering.
Responsibilities
- Lead the AI platform engineering team and own platform reliability, security, scalability, and operational health.
- Translate architecture into maintainable solutions and implement standards using automated testing, quality gates, deployment tooling, and operational-readiness practices.
- Lead cloud platform, CI/CD, and AI workload deployment practices; define monitoring, logging, and observability standards.
- Partner with security, infrastructure, and architecture teams to meet enterprise standards and balance delivery priorities, stability, and technical debt.
- Mentor platform engineers; provide AI teams with reusable services, templates, frameworks, and documentation.
- Review high-risk changes, guide complex decisions, evaluate new technologies, and promote knowledge sharing and engineering best practices.
Qualifications
- At least 8 years in software engineering, platform engineering, cloud engineering, machine learning engineering, or a related technical discipline.
- Demonstrated technical leadership for enterprise platforms, distributed systems, or cloud-native solutions, and production experience with AI, machine learning, or generative AI.
- Strong understanding of software engineering, distributed systems, APIs, microservices, event-driven architectures, and cloud-native development.
- Experience with at least one major cloud platform; AWS is preferred, while Azure or GCP experience is welcomed.
- Experience with Infrastructure as Code, containerization, modern deployment practices, CI/CD, automation, monitoring, and enterprise operations.
- Understanding of AI platform components such as vector databases, retrieval systems, orchestration frameworks, or model serving.
- Experience with engineering standards, governance, operational processes, platform security, access management, risk, cost, or operational governance.
- Strong communication and stakeholder-management skills, plus experience mentoring engineers.
- Familiarity with agentic AI, AI orchestration frameworks, or emerging AI platform capabilities is beneficial.
Candidate approach
Waters welcomes experienced engineering leaders with production AI delivery experience even if they have not used every listed tool or framework.
The successful candidate can continue developing skills as the AI platform, tooling, and operating model mature.
Compensation
- Listed salary range is USD 152,000–253,000 yearly.
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