> Markdown version of [/jobs/ext/3859013-principal-ai-solutions-architect-reporting-to-vp-of-software-engineering](https://www.wearedevelopers.com/jobs/ext/3859013-principal-ai-solutions-architect-reporting-to-vp-of-software-engineering). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md).

---

# Principal AI Solutions Architect reporting to VP of Software Engineering

- **Company:** NASDAQ Stock Market
- **Location:** London, UK
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** LangGraph Framework, Java (Programming Language), Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Software Applications, Microsoft Azure, Continuous Integration, Distributed Systems, Enterprise Architecture Framework, Spring Framework, PostgreSQL, OpenAI, Software Engineering, Workflow Management Systems, Pinecone, Enterprise Software Applications, Retrieval-Augmented Generation, Large Language Models, Multi-Agent Systems, Spring-boot, IT Architecture, HybridCloud, Agentic-AI, Event Driven Architecture, Pgvector, Containerization, Kubernetes, Weaviate, Enterprise Integration, Restful APIs, Domain Driven Design, Semantic Kernel, Oracle Cloud Infrastructure, OpenSearch, Microservices
- **Published:** October 22, 2026
- **Apply:** https://startup.jobs/principal-ai-solutions-architect-nadq-nasdaq-inc-10540324

## About the Role

You'll thrive in this position if you're an experienced architect who is actively exploring and applying AI in enterprise environments, comfortable working across cloud, hybrid, and distributed systems, and passionate about translating emerging AI capabilities into practical, scalable solutions. We value adaptability and intellectual curiosity as much as deep technical expertise., * Several years of software engineering and architecture experience, including 5+ years designing large-scale distributed systems, with a strong foundation in Java, Spring Boot, and enterprise application design.

 * Demonstrated experience with AI architecture patterns including agentic workflow design, RAG architectures, LLM integration, vector databases, and AI orchestration frameworks (e.g., Spring AI or comparable).

 * Proven ability to design and deliver cloud-native and hybrid-cloud solutions across platforms such as AWS, Azure, OCI, or GCP, including Kubernetes, container platforms, and CI/CD pipelines.

 * Strong understanding of microservices, event-driven systems, API governance, domain-driven design, and enterprise integration architectures.

 * Clear communicator with a track record of influencing engineering, product, infrastructure, and executive leadership teams across complex, matrixed organizations.

Preferred Qualifications

 * Familiarity with AI ecosystems such as LangGraph, Semantic Kernel, OpenAI, Azure OpenAI, or Anthropic, and/or vector stores such as Pinecone, Weaviate, OpenSearch, or PostgreSQL pgvector.

 * Experience building AI-powered applications in regulated industries, including financial services or trading environments.

 * Knowledge of enterprise architecture frameworks, governance models, and developer experience practices.

This position is based in London and offers a hybrid work environment with at least 3 days per week in-office, subject to change.

## Description

* Define and lead the enterprise AI architecture strategy, designing agentic workflows, multi-agent systems, and LLM integration patterns that automate complex business processes across customer-facing and internal platforms.

 * Architect scalable, resilient solutions using Java, Spring Boot, Spring AI, REST APIs, event-driven architectures, and microservices - establishing reference implementations that accelerate AI adoption across engineering teams.

 * Participate actively in enterprise architecture forums, ensuring AI initiatives align with application, integration, security, and infrastructure standards across hybrid cloud and on-premises environments.

 * Define governance, observability, and responsible AI controls - including model lifecycle management, prompt security, data protection, and compliance frameworks - in close partnership with security and compliance teams.

 * Mentor engineers, architects, and technical leads, acting as a trusted advisor to senior technology leadership and driving architectural consistency across multiple products and platforms.