About Gruve Gruve is an innovative software services startup dedicated to transforming enterprises to AI powerhouses. We specialize in cybersecurity, customer experience, cloud infrastructure, and advanced technologies such as Large Language Models (LLMs). Our mission is to assist our customers in their business strategies utilizing their data to make more intelligent decisions.

As a well-funded early-stage startup, Gruve offers a dynamic environment with strong customer and partner networks.

About The Role

We are seeking a Technical Solution Architect to lead the design, governance, and implementation of AI-driven software solutions for our client. In this role, you will partner closely with business and engineering teams to architect scalable AI-enabled platforms that move AI initiatives from concept to production. You will define the enterprise architecture for AI, data, and software systems, ensuring interoperability, governance, security, and alignment with business strategy in a complex, regulated environment.

This is a highly strategic and hands-on role requiring expertise in modern AI architectures, cloud platforms, large language models (LLMs), data platforms, and enterprise software design.

Key Responsibilities

Define and drive the AI software architecture, technology strategy, and long-term roadmap. Design scalable AI, data, and application architectures that support analytics, AI/ML, LLMs, and partner integrations. Partner with business and engineering stakeholders to align architecture with enterprise goals.

Enable AI readiness through governed, discoverable data and automated data pipelines. Evaluate and recommend enterprise AI platforms, LLMs, vector databases, graph databases, and orchestration frameworks. Establish architecture standards, governance models, and best practices across development teams.

Design APIs, microservices, and event-driven architectures to support modern AI applications. Define data governance, security, compliance, and risk management strategies for AI solutions. Collaborate with security teams to protect AI, ML, and enterprise data assets.

Lead technology evaluations, proof of concepts, and architecture reviews. Monitor emerging AI technologies and continuously evolve the enterprise architecture. Provide technical leadership and mentor engineering teams on architecture best practices.

Qualifications

Bachelor's degree in Computer Science, Data Science, AI/ML, Information Systems, or a related field (or equivalent practical experience). 6+ years of experience in Solution Architecture, Data Architecture, or Enterprise Architecture. Experience designing and implementing AI-driven enterprise software solutions.

Hands-on experience with machine learning frameworks such as TensorFlow or PyTorch. Experience with cloud AI platforms including AWS SageMaker, Azure ML, or Google Vertex AI. Experience working with Large Language Models (LLMs) such as Claude, ChatGPT, or Gemini.

Strong knowledge of: Vector databases Graph databases Retrieval-Augmented Generation (RAG) Model Context Protocol (MCP) AI Agents MLOps Experience with APIs, microservices, and event-driven architectures. Knowledge of AI/ML observability including model monitoring, latency, drift detection, and quality metrics. Understanding of AI FinOps, including AI infrastructure, inference, and token cost optimization.

Experience working within regulated industries and compliance frameworks (HIPAA, FHIR, EDI, or similar). Strong communication, leadership, and stakeholder management skills.

Preferred Qualifications

Master's degree in Computer Science, Data Science, AI/ML, or a related field. Experience selecting, fine-tuning, and deploying foundation models. Experience building enterprise AI governance frameworks.

Expertise in enterprise architecture methodologies and best practices. Experience evaluating vendor-neutral AI technologies and enterprise platforms.