Overview
The AI Solutions Architect designs scalable, secure, and business-aligned AI architectures across implementations and modernization initiatives.
This role defines the technical blueprint for enterprise AI adoption, ensuring solutions are production-grade, cost-efficient, and aligned with client strategy.
Your Role and Responsibilities
What You’ll Do
Key Responsibilities
- Define reference architectures for AI, GenAI, and data platforms across client engagements.
- Lead technical discovery and translate business goals into solution designs.
- Select the right models, frameworks, and cloud services for each use case.
- Establish standards for security, governance, cost control, and responsible AI.
- Guide engineering teams through implementation and review technical deliverables.
- Partner with sales and delivery to scope, estimate, and de-risk proposals.
- Stay ahead of the AI landscape and evangelize best practices internally and with clients.
REQUIREMENTS
What This Role Requires
Education
- Bachelor’s or Master’s degree in Computer Science, Data Science, or a related
field.
Experience
- 6+ years in software/solution architecture, with at least 2 years focused on AI/ML or data platforms.
- Experience delivering enterprise-scale cloud solutions.
- Track record of leading multi-disciplinary technical teams.
Technical Skills
- Deep knowledge of cloud AI services (AWS Bedrock/SageMaker, Azure OpenAI, Google Vertex AI).
- Strong grasp of LLM architectures, RAG, vector databases, and MLOps.
- Proficiency in Python and modern data stack tooling.
- Understanding of enterprise integration, microservices, and event-driven design.
- Familiarity with security frameworks and data governance.
Soft Skills
- Strong leadership and stakeholder management.
- Excellent communication with both executives and engineers.
- Structured, analytical problem-solving.
- Comfort making trade-off decisions under uncertainty.
Working at Motivus
What Working Here Looks Like
- Guild community: You’re part of the [Data & AI / Backend / Cloud] Guild — a community of practitioners in your domain. Structured learning, peer review, and certifications happen here, not in isolation.
- Outcome accountability: Your work connects directly to a client result. We don’t measure activity — we measure delivery.
- AI in your workflow: Through AI Champions and Guild initiatives, you’ll actively use and shape how AI tools are applied to engineering work — not just hear about it in a townhall.
- Defined career path: Structured progression from individual contributor to technical lead to Guild leadership, with certifications and milestones that are visible, not arbitrary.
