Solutions Architect 5 AI Architect

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., Please read these Terms & Conditions (“Agreement”, “Terms”) carefully before using the Candidate Portal (“Portal”, “Service”) provided by The AES Group (“we”, “us”, “our”).

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If you do not agree with any part of these Terms, you may not use the Portal.

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1. Termination

• Bachelor’s 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 (GCP).
• 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)