GenAI Solutions Architect - SFL Scientific
- Work with clients to design, architect, and implement AI-enabled solutions from inception to production deployment
- Define client GenAI/AI strategy and technical architecture
- Stay ahead of industry trends, evaluate new tools/features, pilot innovative solutions, and shape roadmaps for client-facing GenAI tools
- Lead technical strategy and blueprinting of AI/GenAI systems, aligning solution architecture with business objectives, security, and scalability requirements
- Collaborate with data scientists, engineers and domain experts to integrate AI outputs into software and product workflows
- Oversee deployment of AI applications into production environments, ensuring performance optimization, model monitoring, version control and continuous improvement
- Participate in architectural and deployment discussions to ensure solutions are designed for successful scale, security, and high availability in the cloud or on prem
- Mentor, motivate, and coach junior members on technical best practices and inspire professional development
- Ability to work independently and collaborate as part of a team
- Effective written and verbal communication skills
- Meticulous attention to detail and quality of work product
- Ability to build and sustain professional relationships
- Ability to lead projects or workstreams
- Ability to manage and prioritize multiple tasks in a fast-paced and dynamic environment
- Strong interpersonal skills and professional demeanor
- Ability to meet deadlines
- Ability to provide clear guidance to others
- Bachelor's degree in a relevant STEM field (Computer Science, Engineering, Physics, etc.)
- 4+ years of experience in designing and implementing cloud-native AI architectures (AWS, Azure of GCP)
- 4+ years of specific technology domain areas (i.e., software development, cloud computing, systems engineering, infrastructure, security, networking, data & analytics) experience
- 4+ years of programming in Python with modern packages (i.e., Docker, Kubernetes, Airflow, Kafka, etc.)
- 3+ years of design, implementation or consulting in deploying AI applications with unit and integration testing in enterprise systems and supporting data pipelines, leveraging event-driven or microservices-based architectures
- Live within commuting distance to one of Deloitte's consulting offices
- Ability to travel 10%, on average, based on the work you do and the clients and industries/sectors you serve
- Limited immigration sponsorship may be available
- Master's degree in Computer Science, Engineering or Physics, etc. or related STEM field
- AWS/Azure Certifications (AWS/Azure Certified: Sys Ops Administrator, Dev Ops Engineer, Solutions Architect)
- 3+ years of experience deploying AI solutions in regulated or mission-critical industries (i.e., healthcare, life sciences, finance)
- 2+ years of experience applying enterprise AI governance, bias mitigation and performance optimization techniques (scaling, configuration, management) in production AI systems
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