Solutions Architect 5 AI Architect
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Job description
Our client is seeking a highly experienced AI Solutions Architect for an enterprise AI architecture opportunity with one of our clients, a leading global organization in the manufacturing industry.
The ideal candidate will bridge business requirements and technical execution by defining scalable, secure, and production-ready AI and Generative AI solutions.
This is a senior-level architecture position focused on technical discovery, enterprise solution design, technology evaluation, architectural strategy, and implementation guidance across hybrid cloud and on-premises environments.
The role emphasizes enterprise AI architecture and technical leadership rather than hands-on machine learning model development or day-to-day application coding., * Partner with enterprise architects, business stakeholders, and technical teams to identify AI, Generative AI, and data-driven business opportunities.
- Lead business and technical discovery sessions to understand objectives, functional requirements, constraints, and expected outcomes.
- Translate business requirements into scalable enterprise solution architectures and actionable technical implementation strategies.
- Architect enterprise AI solutions incorporating Retrieval-Augmented Generation (RAG), vector databases, enterprise search, prompt orchestration, Agentic AI, and multi-agent workflows.
- Evaluate AI platforms, architectural alternatives, integration patterns, technical dependencies, implementation risks, and technology feasibility.
- Provide architectural direction and technical guidance to engineering teams throughout solution planning and implementation.
- Collaborate with AI engineers, data scientists, ML engineers, application developers, and business domain experts.
- Develop lightweight prototypes and reference implementations to validate architectural recommendations and demonstrate solution patterns.
- Recommend enterprise AI platforms, cloud services, APIs, SDKs, and reusable integration architectures.
- Ensure architecture designs align with enterprise security, identity management, governance, compliance, and technology standards.
- Develop architecture diagrams, technical documentation, design specifications, and implementation guidelines.
- Establish reusable enterprise AI reference architectures, design patterns, and solution accelerators to support organization-wide AI adoption.
Requirements
- Bachelorβs degree with 10+ years of relevant professional experience in enterprise solution architecture, AI architecture, or related technical architecture roles.
- Demonstrated experience designing and implementing enterprise AI and Generative AI solutions.
- Strong understanding of enterprise AI architecture concepts, including:
- Natural Language Processing (NLP)
- Retrieval-Augmented Generation (RAG)
- Vector databases and vector search
- Enterprise search architectures
- Prompt engineering and orchestration
- Agentic AI and multi-agent workflows
- AI model integration and production deployment patterns
- Proven ability to conduct business and technical discovery sessions and translate requirements into enterprise architecture solutions.
- Experience designing scalable architectures across hybrid on-premises and cloud environments.
- Working knowledge of at least one major cloud platform: Microsoft Azure, AWS, or Google Cloud Platform (Google Cloud Platform).
- Strong understanding of modern application and integration architectures, including APIs, microservices, containers, cloud-native solutions, and enterprise security integration.
- Ability to develop lightweight prototypes and reference implementations to demonstrate architectural approaches.
- Working knowledge of Python, JavaScript/TypeScript, REST APIs, SDKs, and development notebooks.
- Experience providing architectural direction and implementation guidance to engineering and development teams.
- Excellent communication, stakeholder management, technical facilitation, and cross-functional collaboration skills.
Preferred Qualifications
Experience with one or more of the following technologies and platforms is highly desirable.
Enterprise AI Platforms
- Azure OpenAI
- Amazon Bedrock
- Google Vertex AI
- AI Refinery
- Microsoft Foundry
AI Frameworks and Architecture
- LangChain
- LangGraph
- GraphRAG
- Agent Skills
- Agent Harness Patterns
- Model Context Protocol (MCP) Servers
- Multi-agent orchestration
Data Platforms
- Snowflake
- Dataiku
Cloud and Container Technologies
- Kubernetes
- Azure Kubernetes Service (AKS)
- Amazon Elastic Kubernetes Service (EKS)
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