AI Solutions Architect
Spruce Infotech
This role serves as a senior technical leader responsible for designing scalable AI solutions and guiding initiatives from concept through production. The AI Solutions Architect will partner with business stakeholders, engineering teams, and data resources to translate requirements into practical architectures, ensuring solutions are aligned with enterprise standards and built for long-term scalability. This individual will also contribute to establishing best practices, integration patterns, and governance approaches across a growing portfolio of AI initiatives.
Key Responsibilities- Design end-to-end architectures for AI-driven applications, including data flows, APIs, and system integrations
- Partner with business and technical stakeholders to translate requirements into scalable solution designs
- Provide architectural guidance across multiple AI initiatives, ensuring alignment with enterprise standards and best practices
- Define and promote reusable patterns for AI development, integration, and deployment
- Support architecture reviews, identifying risks related to scalability, security, and performance
- Design and standardize integration approaches across enterprise systems and external services
- Collaborate with engineering and data teams to ensure solutions are production-ready and maintainable
- Contribute to documentation including architecture diagrams, technical designs, and solution overviews
- Evaluate emerging AI tools, platforms, and frameworks and provide recommendations for adoption
- 8+ years of experience in solutions architecture, software engineering, or related technical roles
- Strong experience designing and delivering complex, multi-system solutions in cloud environments
- Understanding of AI/ML concepts, including LLMs and modern AI application patterns
- Experience with API design, data integration, and distributed system architecture
- Familiarity with cloud platforms (AWS, Azure, or GCP) and modern development practices
- Strong communication skills with the ability to work across technical and business stakeholders
- Experience supporting AI/ML or GenAI initiatives in production environments
- Familiarity with platforms such as OpenAI, Claude, Gemini, or similar AI frameworks
- Exposure to data platforms (e.g., Snowflake, BigQuery) and modern data architectures
- Experience with event-driven architectures, microservices, or integration platforms
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