As a Solutions Architect, you will lead the advertising industry by enabling clients to realize the full potential of Metaβs solutions and even defining new solutions. You will work with companies on their identity and advertising initiatives, translating their business goals into an execution plan using Metaβs suite of cutting-edge advertising platforms. This role will allow you to apply your passion for problem solving to achieving real-world marketing results at Meta scale.
Responsibilities
Understand business challenges to define and drive strategies to help businesses onboard enterprise solutions
Use broad range of technical and soft skills to build productive relationships with our partners, and esolve complex technical and business needs
Understand and apply knowledge of products, technologies and business to build solutions to solve for problems at scale
Break down coding projects into tasks and partner with all applicable teams and partners to meet pre-established goals
Build relationships with team members and cross functional partners
Influence decision-making through presentation of data-centric business topics
Participate in interviewing and on-boarding of new team members
Minimum Qualifications
Currently has, or is in the process of obtaining a Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
Experience working with Enterprise Identity Management platforms, SSO alongside SaaS systems. Experience with SAML/SCIM
Technical background allowing to understand and advise on enterprise architecture, cloud systems, security, and integration. Identity and access management (IAM) expertise
Experience communicating with technical and business audience at prospects or clients
Experience working in highly collaborative and ambiguous environments
Experience demonstrating knowledge of industry technology areas and trends
Preferred Qualifications
Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)
Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)
Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies