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Expert Enterprise AI Solutions Designer
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The role of AI Solution Architect plays a critical part in translating business needs into actionable architecture and technical designs. In this position, you will be responsible for designing and integrating end-to-end AI workflows that are robust, scalable, and span data ingestion, model deployment, API orchestration, and business system integration across hybrid cloud and on-prem environments.
- Design end-to-end AI solutions that are secure, scalable, and aligned with business goals.
- Architect and deliver solutions for the AI platform, encompassing Agentic AI, AI Workbench and Tooling, Model Garden, and AI Runtime environments.
- Translate business needs into technical architecture, including selecting appropriate tools, frameworks, and infrastructure for AI model development and operations.
- Integrate AI capabilities with internal APIs, enterprise platforms and user-facing applications in IT and Networks.
- Evaluate and recommend AI platforms and tools based on enterprise goals and technical fit.
- Collaborate with engineering and data teams to operationalize AI models, ensuring architectural alignment, scalability, and lifecycle support.
- Define and enforce architectural standards, reusable design patterns, and reference implementations to streamline AI deployment across business units.
- Provide technical leadership in prototyping, experimentation, vendor technology evaluations, and innovation pilots.
- Stay updated on emerging AI technologies and assess their applicability within the enterprise.
- Bachelor's or Master's degree in Computer Science, Engineering, Data, AI/ML, or related field.
- More than 5 years of experience in solution architecture or technical leadership roles, with a strong focus on AI platform integration and API-driven systems.
- Proven expertise in designing and integrating end-to-end AI workflows, including data pipelines, model orchestration, and serving APIs across hybrid cloud environments.
- Strong background in designing AI/ML systems, cloud-native architectures, and API ecosystems.
- Hands-on experience with cloud-based AI services such as Microsoft Azure ML, AI Foundry, AWS SageMaker, Bedrock, including model deployment, monitoring, and scaling.
- Experience with tools and frameworks such as LangChain, LangGraph, GraphRAG, Retrieval-Augmented Generation (RAG), MLflow, Kubeflow, and related AI/ML orchestration technologies.
- Proficient in API architecture and integration standards (REST, GraphQL, gRPC).
- Strong understanding of containerization, virtual machines, microservices, and MLOps tools.
- Demonstrated ability to evaluate and integrate new AI technologies, frameworks, and vendor solutions into enterprise environments.
- Effective collaboration skills to work across data, platform, and cybersecurity teams.
- Good internal (IT, Networks, business) and external (suppliers, government) stakeholders management skills.
- Strong technical writing and presentation skills.
- Proactive and fast learner with a strong drive to stay current on emerging technologies and industry trends.
- Full suite of health and wellness benefits.
- Ongoing training and development programs.
- Internal mobility opportunities.
- Support for career growth and professional development.
Our company is committed to a safe and healthy environment for our employees & customers.
