AI & ML Solutions Architect

The Platform Infrastructure Engineering Team at FactSet is looking for an AI & ML Solutions Architect to join the Public Cloud Team to help enable our Generative AI & Machine Learning efforts through the use of Cloud Technologies. This candidate will join a team of Cloud Architects focused on enabling Public Cloud for FactSet’s developer community and products. This team provides consultative services, hands-on support and platform architecture for FactSet’s cloud program. The team works to balance developer velocity and meet the overall need for stability, performance, cost and security of FactSet services running in the cloud. This person will have a specific focus on Gen AI and ML, helping to lead the way in identifying, integrating and adopting these key technology opportunities for our stakeholders.

Responsibilities:

Help pioneer the adoption of Generative AI, AI and Machine Learning Services
Identify opportunities for AI technology to enhance current application workflows or enable new ones.
Architect Cloud AI services for performance, stability, security & compliance
Supports the planning and implementation of enterprise Cloud Programs
Assist engineering teams in migrating their services to Public Cloud.
Internal client facing support & services; promotes a client-centric culture within the team.
Fosters a culture of innovation and encourages colleagues to think differently in finding solutions.
Work with other Platform Infrastructure Engineering teams to help drive adoption of Cloud services by ensuring core FactSet Infrastructure services are available in the cloud and easily consumable by FactSet engineering teams.
Increase velocity of cloud migration and digital transformation by helping engineering teams adopt DevOps, Infrastructure as Code, and automated release processes.
Work with FactSet security organization to ensure a strong security posture of services and data in the cloud.
Identify and implement cost optimization strategies for cloud services.

Minimum Requirement: Requirements:

5+ years Public Cloud experience working in a highly distributed fast paced environment.
5+ years working knowledge of one or more of the following: Python, GoLang, Terraform, CloudFormation, or Ansible.
1+ year working experience with a primary focus on AI & ML services.

Critical Skills:

Certification in AWS, Azure or GCP
Experience working with Cloud AI technologies, examples which may include: Open AI, Azure Open AI, AWS Sagemaker, GCP Vertex or other similar cloud AI, ML & cognitive services.
Experience with Containers & Serverless.
Foundational knowledge on core cloud computing

Additional / Preferred Skills:

Strong desire for learning new tech and solving challenging engineering problems.
Strategic, analytical, and creative thinking style with a realistic, pragmatic approach

Education: