Principal AI Solutions Architect

Key Responsibilities

• 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.

Required Qualifications

• 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.

Benefits & Rewards

We offer a competitive, well-rounded rewards package designed to support the financial, physical, and emotional well-being of our employees and their families (where applicable).

The actual pay depends on factors like your skills, experience, qualifications, and location. In addition to base pay, we offer short-term incentives (bonus or commission) and long-term incentives (equity), where applicable.

We utilize a structured job architecture and career framework to ensure growth opportunities are transparent, fair, and accessible to all employees. The pay range you see reflects the full salary band for this job level, including room for progression over time.

For more information, visit Nasdaq Benefits & Rewards Career Page.

Come as You Are

Nasdaq is an equal opportunity employer. We welcome applications from candidates of all backgrounds and identities.

We are committed to fostering an inclusive workplace where diverse perspectives, experiences, and identities are valued and celebrated.

We ensure that individuals with disabilities are provided with reasonable accommodation throughout the hiring process.