Overview:
In this role, you will work in a fast-paced, agile environment alongside a diverse team with a passion for technology, transformation, and delivering results.
As part of the Waters AI Center of Excellence (CoE), you will help define and govern our enterprise AI architecture, creating the standards, patterns, and guardrails needed to scale AI solutions across the business. This includes generative AI, machine learning, automation, and future agent-based capabilities.
This is a senior, hands-on role. You'll work closely with teams across IT, Data, Security, and the business to shape AI strategy, review solution designs, establish best practices, and ensure AI solutions are secure, scalable, and aligned to business objectives.
We understand that very few people will have deep expertise across every area of enterprise AI. We're looking for someone with a strong architecture background and proven experience delivering AI solutions in a business environment. For the right person, we're prepared to invest in development and provide opportunities to build expertise in newer areas of AI as our capabilities continue to grow.
Here at Waters, we look for people who enjoy solving complex problems, can work effectively across teams, and stay focused on delivering outcomes.
Responsibilities:
- Define enterprise AI architecture across machine learning, generative AI, automation, and emerging agent-based capabilities
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Develop architectural standards, patterns, and reference architectures for AI solutions.
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Work alongside engineering, data, security, and business teams to design scalable and secure AI solutions
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Establish and evolve AI governance processes, ensuring alignment with enterprise standards and long-term technology strategy
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Review AI solution designs and provide architectural guidance throughout delivery.
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Establish engineering standards covering code quality, testing, automation, deployment, and operational readiness
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Lead proof-of-concepts and technical evaluations of new AI technologies and platforms
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Support the development of operational approaches for deploying, monitoring, and maintaining AI solutions in production
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Partner with security and governance teams to ensure AI solutions meet regulatory, compliance, and data protection requirements
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Promote responsible and secure use of AI across the organization
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Provide technical leadership and mentoring within the AI CoE and wider technology community
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Stay informed on AI developments and assess their relevance to Waters
Qualifications:
- Bachelor's or Master's degree in a relevant field or equivalent practical experience.
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10 years + experience in enterprise, solution, cloud, data, or application architecture roles
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Proven experience designing, implementing, or supporting AI, machine learning, or generative AI solutions within an enterprise environment
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Strong understanding of modern AI architecture concepts such as RAG, semantic search, vector databases, prompt design, and AI integration patterns
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Experience with at least one major cloud platform (AWS, Azure, or GCP)
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Understanding of the lifecycle and operational management of AI solutions in production environments
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Hands-on experience with Python and common AI/ML tooling
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Strong understanding of APIs, distributed systems, microservices, and modern software architecture principles
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Experience working with data platforms, data pipelines, and enterprise data architectures
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Exposure to agentic AI, AI orchestration frameworks, intelligent automation, or related technologies would be beneficial
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Understanding of AI governance, security, risk, and Responsible AI principles.
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Strong communication skills and the ability to engage effectively with both technical and non-technical stakeholders
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Experience influencing technical direction, facilitating workshops, and mentoring others
Please don't rule yourself out. We're looking for strong architects with practical AI experience who can help us build and scale AI capabilities across Waters. While experience in AI is important, we don't expect candidates to have worked with every technology, framework, or architectural approach listed above. If you've successfully delivered AI, machine learning, data science, or generative AI solutions and have a solid architecture background, we'd encourage you to apply. We'll support the successful candidate with ongoing development as our AI capabilities continue to evolve
Company Description:
Waters Corporation (NYSE:WAT) is a global leader in life sciences and diagnostics, dedicated to accelerating the benefits of pioneering science through analytical technologies, informatics, and service. With a focus on regulated, high-volume testing environments, our innovative portfolio harnesses deep scientific expertise across chemistry, physics, and biology. We collaborate with customers around the world to advance the release of effective, high-quality medicines, ensure the safety of food and water, and drive better patient outcomes by detecting diseases earlier, managing routine infections, and combating antibiotic resistance. Through a shared culture of relentless innovation, our passionate team of ~16,000 colleagues turn scientific challenges into breakthroughs that improve lives worldwide.
Diversity and inclusion are fundamental to our core values at Waters Corporation. It benefits our employees, our products, our customers and our community. Waters complies with all applicable federal, state, and local laws. Qualified applicants are considered without regard to sex, race, color, ancestry, national origin, citizenship status, religion, age, marital status (including civil unions), military service, veteran status, pregnancy (including childbirth and related medical conditions), genetic information, sexual orientation, gender identity, legally recognized disability, domestic violence victim status, or any other characteristic protected by law. Waters is proud to be an equal opportunity workplace and is an affirmative action employer. All hiring decisions are based solely on qualifications, merit, and business needs at the time.
Key Words: Enterprise Architect; Solution Architect; Agentic AI; GenAI; RAG; Architecture Governance; Data Architecture; AI Platform
