AI Solution Architect

Role: AI Solution Architect

Location: Onsite Tampa Florida

Duration: Fulltime

Experience: 8 15 years of overall IT experience with at least 3 5 years focused on AI solution architecture and delivery.

Mandatory Skill Tags: AI Solution Architecture AI solution design latest AI models LLMs enterprise AI architecture cloud AI/ML platforms data & MLOps integration

Secondary Skill Tags: responsible AI AI governance vector databases RAG semantic search MLOps tools cloud-native architecture microservices Kubernetes agile delivery

Job Summary:

The Onsite AI Solution Architect will lead the end-to-end architecture design and implementation of AI and AI-native solutions for Advantive. This role will closely collaborate with business stakeholders product owners data teams and engineering to translate business requirements into scalable secure and robust AI architectures. The architect will provide thought leadership on latest AI models and LLMs and ensure best practices governance and standards are adopted across AI initiatives.

Key Responsibilities:

• Lead the architecture design and technical roadmap for AI and AI-native solutions aligned to Advantives business strategy.
• Translate business and functional requirements into scalable AI solution architectures covering data model application and integration layers.
• Evaluate select and integrate latest AI models and LLMs (including cloud and third-party services) into enterprise applications and workflows.
• Define reference architectures patterns standards and reusable components for AI solution delivery across the organization.
• Collaborate with data engineers MLOps engineers application developers and product teams to ensure high-quality production-grade AI deployments.
• Establish non-functional requirements (performance security reliability observability) and ensure AI solutions meet enterprise architecture and compliance guidelines.
• Conduct technical reviews PoCs and feasibility assessments for new AI use cases and guide teams on best practices and optimization.
• Provide architectural leadership mentoring and guidance to project teams driving continuous improvement and innovation in AI solution delivery.

Required Skills:

• Strong experience in AI Solution Architecture designing and delivering enterprise-grade AI solutions.
• Proven expertise in architectural design involving AI solutions including end-to-end solution blueprints and reference architectures.
• Hands-on knowledge of designing AI-based solutions using machine learning deep learning and LLM-based approaches.
• In-depth understanding of latest AI models and large language models (LLMs) including their capabilities limitations and suitable use cases.
• Experience with AI/ML platforms and services (e.g. Azure AI AWS AI/ML Google Cloud AI or equivalent).
• Solid understanding of data architecture concepts including data pipelines feature stores model deployment and monitoring (MLOps).
• Strong background in application integration patterns (APIs microservices event-driven architecture) for embedding AI into products and workflows.
• Ability to create high-quality architectural artifacts (HLDs LLDs sequence diagrams data flow diagrams) and communicate them to technical and non-technical stakeholders.
• Strong stakeholder management communication and leadership skills to drive consensus and decision-making.

Good to Have Skills

• Experience with AI governance model risk management and responsible AI practices (fairness explainability security and privacy).
• Familiarity with vector databases semantic search RAG (Retrieval-Augmented Generation) and knowledge-graph-based solutions.
• Exposure to MLOps tools and frameworks for CI/CD of ML models and LLM-based applications.
• Experience in designing multi-tenant cloud-native architectures using containers and orchestration (Docker Kubernetes).
• Knowledge of enterprise integration with ERP/CRM/line-of-business applications.
• Prior experience in leading AI architecture for product-based or ISV organizations.
• Experience working in agile delivery environments and collaborating with distributed teams.

Educational Qualification

Bachelors or Masters degree in Computer Science Information Technology Engineering or a related discipline from a recognized institution.