Job Summary

Design and guide the delivery of secure, scalable and reliable enterprise AI solutions. Work closely with business and technology teams to translate business needs into practical architecture, shared capabilities and reusable components. This is a hands-on role combining system design, prototyping, technical evaluation and implementation guidance to help teams move AI solutions from experimentation into production.

Job Responsibilities*

• Develop AI architecture blueprints, technical standards and reusable design patterns aligned with enterprise technology and business requirements
• Translate use-case requirements into solution designs, integration specifications and phased implementation plans
• Design AI applications incorporating language models, enterprise knowledge, AI agents and workflow automation
• Define integration approaches for enterprise applications, data platforms and internal or external AI services
• Build prototypes and reference implementations to validate architecture choices, address technical risks and guide engineering teams
• Evaluate AI technologies, vendor platforms and open-source components against functional requirements, security, performance, interoperability and total cost
• Design for identity and access management, data protection, human oversight, auditability and safe failure handling
• Establish technical requirements for evaluation, testing, monitoring, reliability and cost management throughout the solution lifecycle
• Review technical designs and code, support production-readiness assessments and help resolve complex integration or performance issues
• Work with enterprise architecture, infrastructure, cybersecurity, data governance and Responsible AI teams to meet relevant standards and approval requirements
• Maintain architecture documentation and decision records, and communicate technical options and trade-offs clearly to stakeholders

Qualifications

• Degree in Computer Science, Engineering, Information Technology or a related field, or equivalent practical experience
• Strong experience designing and delivering enterprise software, AI applications or shared technology platforms into production
• Hands-on software development skills with experience in APIs, automated testing and code review
• Practical experience with LLM applications, retrieval-augmented generation, embeddings, vector databases, agent workflows and tool integration
• Strong understanding of distributed systems, enterprise integration and cloud or container-based deployment
• Experience with CI/CD, application observability, performance testing and production troubleshooting
• Understanding of enterprise security, identity and access controls, data privacy and responsible AI practices
• Ability to assess trade-offs across solution quality, scalability, reliability, latency, cost and maintainability
• Strong communication and collaboration skills, with the ability to work across technical teams and business stakeholders