Principal AI Architect
$141k - $222.2kAXA Group
The Principal AI Architect to design and lead the technical strategy for our AI infrastructure, platforms, and systems. In this role, you will own the architectural vision for how we build, deploy, and scale AI solutions across the organization. You'll work at the intersection of AI/ML innovation, systems design, and engineering excellence, partnering with product, data science, and infrastructure teams to build robust, scalable, and responsible AI systems.
This is a high-impact technical leadership role ideal for someone who is passionate about AI systems, thinks deeply about architecture and design patterns, and is excited about solving complex technical challenges at scale. What you'll be doing What will your essential responsibilities include? AI Architecture & Systems Design (40%)- Own the end-to-end technical architecture for AI systems, platforms, and infrastructure
- Design scalable, modular, and extensible AI architectures that support multiple use cases
- Define technical standards, best practices, and design patterns for AI development across the organization
- Evaluate and recommend AI/ML frameworks, tools, and technologies (LLMs, vector databases, orchestration platforms, etc.)
- Design solutions for complex challenges: model serving, real-time inference, batch processing, multi-model systems
- Create architecture documentation, diagrams, and technical specifications for cross-functional teams
- Conduct architecture reviews and provide technical guidance on design decisions
- Design and architect AI/ML platforms and infrastructure for scale (training, inference, monitoring, deployment)
- Define MLOps and model lifecycle management practices (versioning, governance, lineage, reproducibility)
- Design data pipelines, feature engineering infrastructure, and data management systems
- Architect solutions for model serving, inference optimization, and latency requirements
- Plan and execute infrastructure upgrades, migrations, and technical debt reduction
- Establish monitoring, observability, and alerting frameworks for AI systems
- Work with DevOps and Infrastructure teams to operationalize AI systems
- Stay at the forefront of AI/ML research and emerging technologies
- Evaluate new models, frameworks, and techniques for strategic relevance and business impact
- Design proof-of-concepts and pilots for emerging AI technologies (generative AI, multimodal models, agents, etc.)
- Provide technical thought leadership on AI strategy and technologydmap
- Mentor data scientists and engineers on architectural best practices and design patterns
- Contribute to technical strategy discussions with product and business leadership
- Lead and mentor senior engineers, architects, and technical leads
- Establish technical vision and roadmap aligned with business objectives
- Drive technical decision-making and architecture governance across AI teams
- Partner with Product to translate business requirements into technical architecture
- Collaborate with Data Science, Engineering, and Infrastructure teams on design and implementation
- Lead design reviews, architecture discussions, and technical problem-solving sessions
- Build and maintain robust relationships with key technical stakeholders
- Design systems and processes to ensure responsible AI practices (bias detection, fairness, explainability)
- Establish governance frameworks for model performance, safety, and ethical deployment
- Design monitoring and alerting for model drift, performance degradation, and fairness metrics
- Navigate regulatory requirements and ensure compliance with AI regulations
- Architect solutions for model interpretability, transparency, and auditability
- Lead technical discussions on AI ethics, safety, and responsible system design
- Extensive software engineering or systems architecture experience
- Moderate hands-on experience designing and building large-scale AI/ML systems
- Proven track record architecting systems that have been deployed to production at scale
- Experience leading technical architecture decisions on complex, mission-critical systems
- Demonstrated expertise in distributed systems, scalability, and performance optimization
- Deep expertise in AI/ML fundamentals, algorithms, and best practices
- Outstanding understanding of modern ML frameworks and tools (TensorFlow, PyTorch, JAX, etc.)
- Proficiency in at least one programming language (Python, Java, C++, Go, etc.)
- Experience with cloud platforms (AWS, GCP, Azure) and containerization (Docker, Kubernetes)
- Robust understanding of data engineering, ETL pipelines, and data infrastructure
- Knowledge of database systems, data warehousing, and query optimization
- Familiarity with API design, microservices, and distributed system patterns
- Strategic thinking with ability to balance innovation and pragmatism
- Outstanding problem-solving skills with ability to break down complex technical challenges
- Excellent communication skills; ability to explain complex concepts clearly
- Leadership presence and ability to influence technical teams and stakeholders
- Intellectual curiosity and passion for staying current with AI/ML research and trends
- Comfort with ambiguity and ability to make decisions with incomplete information
- Robust judgment and ability to make sound architectural trade-offs
- Track record of mentoring senior engineers and technical leads
- Experience navigating organizational and technical complexity at scale
- Thought leadership in AI/ML architecture (speaking engagements, publications, open-source contributions)
- Bachelor's degree in Business, Computer Science, Project Management or a related field. Engineering, computer science, data science, or machine learning background
- Understanding of AI infrastructure, model training, deployment, and MLOps
- Familiarity with prompt engineering, fine-tuning, and LLM customization
- Knowledge of RAG (Retrieval-Augmented Generation), agents, and advanced AI architectures
- Experience in enterprise SaaS, B2B, or B2B2C product management
- Track record in regulated industries (finance, healthcare, enterprise) or compliance-heavy environments
- Previous experience with platform or ecosystem products
- Demonstrated understanding of AI safety, fairness, bias mitigation, governance and responsible AI frameworks
- Knowledge of AI ethics principles and ability to operationalize them in product decisions
- Experience with generative AI, LLMs, or conversational AI products
- Experience with large language models (LLMs), transformers, and generative AI systems
- Expertise in RAG (Retrieval-Augmented Generation), fine-tuning, and prompt engineering
- Experience designing AI agents and multi-step reasoning systems
- Knowledge of model compression, quantization, and inference optimization
- Familiarity with reinforcement learning or other advanced ML techniques
- Experience designing and operating ML platforms (Kubeflow, MLflow, SageMaker, Vertex AI, etc.)
- Expertise in model serving and inference optimization (TensorFlow Serving, Triton, etc.)
- Experience with feature stores and feature engineering platforms
- Knowledge of monitoring, observability, and alerting for ML systems
- Experience with infrastructure-as-code and CI/CD pipelines for ML
- Five Business Resource Groups focused on gender, LGBTQ+, ethnicity and origins, disability and inclusion with 20 Chapters around the globe.
- Robust support for Flexible Working Arrangements
- Enhanced family-friendly leave benefits
- Named to the Diversity Best Practices Index
- Signatory to the UK Women in Finance Charter
Our Pillars:
- Valuing nature: How we impact nature affects how nature impacts us. Resilient ecosystems - the foundation of a sustainable planet and society - are essential to our future. We're committed to protecting and restoring nature - from mangrove forests to the bees in our backyard - by increasing biodiversity awareness and inspiring clients and colleagues to put nature at the heart of their plans.
- Addressing climate change: The effects of a changing climate are far-reaching and significant. Unpredictable weather, increasing temperatures, and rising sea levels cause both social inequalities and environmental disruption. We're building a net zero strategy, developing insurance products and services, and mobilizing to advance thought leadership and investment in societal-led solutions.
- Integrating ESG: All companies have a role to play in building a more resilient future. Incorporating ESG considerations into our internal processes and practices builds resilience from the roots of our business. We're training our colleagues, engaging our external partners, and evolving our sustainability governance and reporting.
- AXA Hearts in Action : We have established volunteering and charitable giving programs to help colleagues support causes that matter most to them, known as AXA XL's "Hearts in Action" programs. These include our Matching Gifts program, Volunteering Leave, and our annual volunteering day - the Global Day of Giving.
For more information, please see Sustainability at AXA XL. Applicants for this role must be legally authorized to work in the United States without sponsorship now or in the future. The U.S. base salary range for this position is USD 141,000 - 222,200.
Actual pay will be determined based upon the individual's skills, experience and location. We strive for market alignment and internal equity with our colleagues' pay.
At AXA XL, we know how important physical, mental, and financial health are to our employees, which is why we are proud to offer benefits such as a competitive retirement savings plan, health and wellness programs, and many other benefits. We also believe in fostering our colleagues' development and offer a wide range of learning opportunities for colleagues to hone their professional skills and to position themselves for the next step of their careers. For more details about AXA XL's benefits offerings, please visit US Benefits at a Glance 2026.
$154.38k - $193.13k
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