AI Solution Architect

Elliott Moss Consulting is looking for an experienced AI Solution Architect to design and oversee scalable, secure and enterprise-ready AI solutions.

The successful candidate will bridge business requirements and technical delivery, leading solution architecture across applications, data, integrations, cloud infrastructure and Generative AI.

Key Responsibilities

• Translate business requirements into technical architecture and detailed design specifications.
• Define solution components, integrations, interfaces and end-to-end data flows.
• Design scalable architectures across application, data, integration and infrastructure domains.
• Design and implement advanced Generative AI frameworks using LangChain, LangGraph and related technologies.
• Develop document ingestion, chunking, embedding, indexing and retrieval pipelines.
• Implement RAG and hybrid-search architectures for enterprise use cases.
• Evaluate technology options and recommend appropriate platforms, tools and architectural approaches.
• Ensure solutions comply with enterprise architecture, cybersecurity, governance and Responsible AI standards.
• Collaborate with engineering, DevOps, data and infrastructure teams throughout implementation and deployment.
• Provide architectural guidance during development, integration, testing and production rollout.
• Engage stakeholders, communicate architectural decisions and manage technical trade-offs.
• Support troubleshooting and provide solution-level guidance throughout project delivery.

Required Experience and Skills

• 5–8 years of relevant technology and solution architecture experience.
• Strong architecture-design capabilities across applications, data, integrations and infrastructure.
• Hands-on experience with Python, LangChain and LangGraph.
• Strong understanding of document-processing pipelines, embeddings, vector indexing, retrieval and hybrid search.
• Experience with at least one major cloud platform: AWS, Microsoft Azure or Google Cloud Platform.
• Strong knowledge of APIs, microservices and enterprise integration patterns.
• Experience designing both monolithic and distributed-system architectures.
• Knowledge of cybersecurity best practices, compliance requirements and enterprise governance.
• Experience with DevOps, CI/CD pipelines, Docker and Kubernetes.
• Practical understanding of Responsible AI principles and their implementation within live AI systems.
• Familiarity with architecture-modelling and documentation tools such as ArchiMate, UML, Lucidchart or Draw.io.
• Strong stakeholder-management, communication and technical leadership skills.

Interested candidates may apply by sharing their updated CV, current location, notice period, current salary and expected salary.