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Technical Solution Architect
Summary by AIEngineer.careers
Technical Solution Architect is a AI Solutions Architect role (full-time). with Gruve. in REMOTE, WORLDWIDE. Compensation shown: $148K–$190K (est.). Imported listing (source: jobs-radar.com). Apply on the employer's site (jobs-radar.com).
Imported listing (source: jobs-radar.com) · Apply on jobs-radar.com
REMOTE · WORLDWIDE
$148K–$190K (est.)
Full-time
SENIOR
The sections below reproduce the third-party job description for reference. AIEngineer.careers does not write or control this text.
Imported job description
Sourced from jobs-radar.com
Gruve is seeking a Technical Solution Architect to lead the design and implementation of AI-driven software solutions for a client. The role involves defining enterprise AI architecture, selecting platforms, and ensuring governance and security. This contract position requires expertise in AI/ML, cloud platforms, and LLMs, with a focus on productionizing AI initiatives.
Responsibilities
- Define and drive AI software architecture and technology strategy
- Design scalable AI, data, and application architectures
- Enable AI readiness through governed data and automated pipelines
- Evaluate and recommend AI platforms, LLMs, and databases
- Establish architecture standards and governance models
- Design APIs, microservices, and event-driven architectures
- Define data governance, security, and compliance strategies
- Lead technology evaluations and proof of concepts
- Provide technical leadership and mentorship
Requirements
- Bachelor's degree in CS, Data Science, AI/ML, or related field
- 6+ years in Solution, Data, or Enterprise Architecture
- Experience designing AI-driven enterprise software
- Hands-on with TensorFlow or PyTorch
Gruve
Redwood City · US · 411+ employees
Gruve is an AI-native enterprise services startup that provides an infrastructure-to-agent platform designed to help enterprises scale AI solutions with measurable outcomes. It differentiates itself from traditional consulting by using AI agents to perform tasks, allowing for usage-based, outcome-oriented pricing rather than hourly billing.
