Senior Manager, Solutions Architecture

Multi-platform familiarity, with expertise in one or more of the following: Front-end: Swift, Kotlin, Maui, React Native, React, Angular, Flutter, Typescript Backend: APIs (NodeJS, Spring, .NET, Python), Cloud (AWS, Azure, GCP), Data Services/Systems (SQL, NoSQL, Kafka) Content management systems, analytics platforms, and other 3rd party frameworks

Front-end: Swift, Kotlin, Maui, React Native, React, Angular, Flutter, Typescript

Backend: APIs (NodeJS, Spring, .NET, Python), Cloud (AWS, Azure, GCP), Data Services/Systems (SQL, NoSQL, Kafka)

Content management systems, analytics platforms, and other 3rd party frameworks

Experience delivering software in an agency/client-service environment

Experience in having commercial conversations involving budgets and fees

Experience with software estimation, work planning, and building project plans within time/cost constraints

Ability to break down complex ideas to both technical and non-technical individuals

You're excited to learn the principles of mobile software development

Experience quickly iterating and refining a product vision with a client by offering multiple approach options

Passion to apply modern processes that transform client organizations (e.g., continuous delivery, rapid iteration, and agile-inspired methodologies)

Excellent verbal and written communication skills

Ability to use repeatable frameworks and best practices to incorporate new technologies or concepts

Appreciation for the wider client enterprise, beyond a single project or initiative

Desire to expand an account to holistically service a client

Equally comfortable working in pre-sale and post-sale environments

An eye for detail and an ability to navigate ambiguity

Experience with leading CCaaS technologies such as Amazon Connect, Zendesk CCaaS, Google CES, Five9, and Genesys CCaaS.

Cloud Data Platforms: Experience with Databricks, Snowflake, or other major cloud data warehousing/lakehouse solutions.

Cloud AI/ML Services: Proficiency with cloud-native AI/ML platforms (e.g., AWS Bedrock / Sagemaker, Azure ML, Google AI Platform/Vertex AI).

Understanding of MLOps principles and tools for continuous integration/continuous delivery (CI/CD) of machine learning models.

Familiarity with containerization (Docker) and orchestration (Kubernetes) for scalable deployments.

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