AI Architect

The AI Architect is expected to:

 

Participate in customer discovery sessions, design workshops, and technical discussions to understand business requirements, user workflows, data sources, and AI opportunities.

Define scalable AI solution architectures using appropriate technologies, models, data sources, integrations, security controls, and deployment patterns.

Translate customer requirements into best-practice AI and LabVantage solution designs, balancing configuration, customization, integration, and AI capabilities.

Design and guide implementation of Generative AI use cases, including intelligent assistants, document intelligence, knowledge search, Retrieval-Augmented Generation, workflow automation, and AI-driven recommendations.

Evaluate the suitability of AI technologies, models, frameworks, and tools based on customer requirements, accuracy, performance, security, maintainability, and cost considerations.

Document high-level solution designs, architecture decisions, technical specifications, data flows, AI evaluation approaches, and implementation guidance for project teams.

Provide technical leadership and hands-on guidance to implementation teams during design, development, testing, deployment, go-live, and post-go-live support.

Establish best practices for AI solution development, including prompt engineering, model evaluation, data governance, observability, guardrails, security, versioning, and monitoring.

Ensure AI solutions are designed with appropriate privacy, access-control, auditability, reliability, and responsible-AI considerations.

Review AI-enabled applications, integrations, configurations, and technical deliverables to ensure they meet LabVantage and customer quality standards.

Partner with LabVantage R&D team to provide feedback on customer requirements, reusable AI capabilities, product enhancements, and emerging market needs.

Mentor and coach technical team members on AI architecture, enterprise integration, design best practices, and delivery methodologies.

Contribute creative ideas, proof of concepts, reusable components, and process improvements that increase the efficiency and quality of PSO project delivery.

 

AI and Technical Architecture Expertise

 

The AI Architect should have strong expertise in the following areas:

Generative AI and Large Language Model application architecture

Retrieval-Augmented Generation, embeddings, vector search, and knowledge retrieval

Prompt engineering, prompt management, model evaluation, guardrails, and hallucination mitigation

AI agents, workflow automation, and human-in-the-loop solution design

Machine learning and predictive analytics concepts

Structured and unstructured data ingestion, transformation, governance, and retrieval

Enterprise API integration, web services, event-driven architecture, and system interoperability

Cloud platforms, cloud-native architecture, containers, and DevOps/CI/CD concepts

Database and data-platform concepts, including relational databases and data security

Application architecture, distributed systems, and enterprise software design patterns

Java-based application development, web development, JavaScript, SQL, and API technologies

AI/ML observability, performance monitoring, quality evaluation, and operational support

 

Knowledge of the following is desirable:

LabVantage LIMS product and configuration capabilities

Laboratory information management systems, laboratory informatics, or scientific software

Laboratory workflows such as sample management, quality management, stability, instrument interfacing, ELN, LES, and system integration

Regulated industries, including life sciences, pharmaceutical, quality, manufacturing, or clinical laboratory environments

Amazon Web Services or comparable cloud platforms

Docker, containers, and CI/CD technologies

Oracle and Microsoft SQL Server

Reporting, ETL, and integration tools

JBoss, WebLogic, WebSphere, Linux, and enterprise application-server environments

 

Customer Focus

The AI Architect will build strong working relationships with internal and external customers. The individual must be able to communicate complex technical and AI concepts clearly to business, scientific, and technical stakeholders. The AI Architect will gain customer confidence by understanding customer business and operational needs, setting realistic expectations, identifying risks and alternatives, and designing scalable solutions that create measurable value. The role may also represent LabVantage in customer demonstrations, technical workshops, pre-sales activities, customer training, and industry events.

Architecture Review, Quality, and Delivery

The AI Architect will oversee the design and quality of AI-enabled solutions delivered by project teams. This includes reviewing architecture, code, integrations, prompts, data-access controls, retrieval quality, model outputs, test approaches, and deployment readiness. The primary objective of this review is to ensure that solutions are secure, maintainable, scalable, reliable, and aligned with established technical and AI best practices. The AI Architect will define and continuously improve standards for architecture review, AI quality evaluation, code review, documentation, testing, deployment, and production support.

Project Implementation and Go-Live Support

The AI Architect’s involvement is critical to ensure the appropriate technical framework, resources, automation, security controls, and support model are in place for implementation, testing, go-live, and post-go-live support.

The AI Architect will guide teams in defining test strategies for AI-enabled solutions, including functional testing, integration testing, security testing, regression testing, performance testing, AI output evaluation, and user acceptance testing. The role will help ensure a smooth transition from development and testing environments to production.

Training and Coaching

The AI Architect will provide mentoring and technical leadership to junior and senior engineering team members. This includes reviewing solution designs, encouraging reuse of components, developing delivery best practices, and supporting skill development in AI, GenAI, enterprise architecture, LabVantage implementation, and customer delivery.

Cross-Functional Collaboration

The AI Architect will work across PSO, Product, R&D, Support, Sales, Quality Assurance, and customer teams. The role will provide input on product enhancements, reusable AI capabilities, technical strategy, customer solution patterns, and high-priority issue resolution.

Contribution to Innovation and Reusable Components

The AI Architect will evaluate and propose technical innovations for the PSO organization. This includes developing proof of concepts, AI reference architectures, reusable components, implementation accelerators, evaluation frameworks, and delivery standards that can be used across multiple LabVantage customer projects.