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.