AI Architect

Broadridge
London
1 year ago
Applications closed

Related Jobs

View all jobs

Artificial Intelligence Architect

Artificial Intelligence Architect

Senior Data Scientist SME & AI Architect

AI Lead, AI Engineer Lead, Generative AI Engineer, Machine Learning Engineer, AI Platform Engineer, NLP Engineer, Applied AI Engineer, AI Integration Specialist, AI Software Engineer, AI Systems Architect, AI Engineer, AI Development Lead,

AI & Data Science Manager / Senior Manager

AI & Data Science Manager / Senior Manager


Broadridge Financial Solutions (NYSE: BR), a global Fintech leader with $5 billion in revenues, provides the critical infrastructure that powers investing, corporate governance, and communications to enable better financial lives. 

Itiviti was acquired by Broadridge in May 2021 and is now Broadridge Trading and Connectivity Solutions. Our combined offering enables simplification and streamlining of all front office, middle office, and post-trade functions — powering connectivity and multi-asset trading across global markets.


We are excited to announce an opportunity for an AI Architect to join our organization as part of our AI Enablement Team. In this technical leadership role, you will play a crucial role in Implementing and designing the solutions that enhance our AI capabilities across the organization. These include industry leading products such asBondGPTandOpsGPTas well as advanced use of AI for productivity across our business functions. Key functions include back office operations, investor communications and software product development, onboarding and support.

As the AI Architect, you will be driving innovation and play a crucial role in designing, developing, and deploying machine learning models and applying GenAI technologies in AI solutions across various business functions. The focus of this role includes the entire model development lifecycle, with an emphasis on MLOps practices to ensure robust and scalable solutions. Additionally, expertise in Generative AI, LLMOps, and AI agents is required to drive advanced AI functionalities within our organization.

Join our dynamic team and be part of a collaborative environment that fosters continuous learning and creativity. If you are experienced AI Engineer and passionate about machine learning, GenAI, and want to contribute to high impact AI projects in Financial Services, we invite you to apply for this position.

Job responsibilities:

  • ML Pipelines & Experimentation: Support Data scientists and data engineers by ensuring production ready data, model pipelines are deployed to production.
  • Manage the entire model lifecycle using the code frameworks developed by AI Platform team for feature engineering, model training/evaluation, versioning, deployment/online serving and monitoring prediction quality.
  • Establish and promote best practices in MLOps to streamline model deployment and monitoring across various environments
  • Provide authoritative guidance on state-of-the-art algorithms, repositories, and GenAI techniques like prompt engineering, RAG, AI agents in Generative AI space (LLMs) & share your experience with optimisation techniques such as quantization, pruning, to minimise training & inference requirements for models.
  • Design and implement effective LLM-tooling, finetuning & response evaluation strategies.
  • Guide teams on the latest AI solution development practices and capabilities, and accordingly refine and improve our model development lifecycle and disseminate best practice learnings to colleagues.
  • Help refine and extend our standards and best practices around Machine Learning – training and testing framework, coding standards, engineering practices.

Qualifications & Skills:

  • Demonstrate a strong understanding of natural language processing methods, including deep learning techniques, knowledge distillation, prompt engineering, and fine-tuning.
  • 5-8 years of Industry experience with minimum 2 years of experience working in AWS & AWS Sagemaker and developing Sagemaker pipelines
  • Knowledge of Jenkins, CloudFormation, terraform code & MLOps practices
  • Exhibit proficiency in Python, software engineering practices, along with expertise in deep learning frameworks (ML/distributed ML frameworks like TensorFlow etc)
  • Possess outstanding communication skills and the ability to collaborate effectively with interdisciplinary teams.
  • Proven experience in the full ML model development lifecycle, including design, deployment, and maintenance.
  • Demonstrated experience with Generative AI technologies and LLMOps practices including in AI Agents and ideally in Agentic frameworks
  • Ability to work collaboratively in a fast-paced, innovative environment.
  • Strong problem-solving skills and a passion for implementing cutting-edge AI solutions.
  • Proficient coding skills and strong software development experience (Spark, Python)
  • Bachelors/Masters or PhD program in Computer Science/Statistics or a related field

About Us

Broadridgeis a global technology leader with trusted expertise and transformative technology, helping our clients and the financial services industry operate, innovate, and grow. We power investing, governance, and communications for our clients – driving operational resilience, elevating business performance, and transforming investor experiences.

Hybrid Flexible at Broadridge

We are made up of high-performing teams that meet in person to learn and collaborate as needed. This role is considered hybrid, which means you’ll be assigned to a Broadridge office and given the flexibility to work remotely.

#LI-Hybrid

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Maths for AI Jobs: The Only Topics You Actually Need (& How to Learn Them)

If you are a software engineer, data scientist or analyst looking to move into AI or you are a UK undergraduate or postgraduate in computer science, maths, engineering or a related subject applying for AI roles, the maths can feel like the biggest barrier. Job descriptions say “strong maths” or “solid fundamentals” but rarely spell out what that means day to day. The good news is you do not need a full maths degree worth of theory to start applying. For most UK roles like Machine Learning Engineer, AI Engineer, Data Scientist, Applied Scientist, NLP Engineer or Computer Vision Engineer, the maths you actually use again & again is concentrated in a handful of topics: Linear algebra essentials Probability & statistics for uncertainty & evaluation Calculus essentials for gradients & backprop Optimisation basics for training & tuning A small amount of discrete maths for practical reasoning This guide turns vague requirements into a clear checklist, a 6-week learning plan & portfolio projects that prove you can translate maths into working code.

Neurodiversity in AI Careers: Turning Different Thinking into a Superpower

The AI industry moves quickly, breaks rules & rewards people who see the world differently. That makes it a natural home for many neurodivergent people – including those with ADHD, autism & dyslexia. If you’re neurodivergent & considering a career in artificial intelligence, you might have been told your brain is “too much”, “too scattered” or “too different” for a technical field. In reality, many of the strengths that come with ADHD, autism & dyslexia map beautifully onto AI work – from spotting patterns in data to creative problem-solving & deep focus. This guide is written for AI job seekers in the UK. We’ll explore: What neurodiversity means in an AI context How ADHD, autism & dyslexia strengths match specific AI roles Practical workplace adjustments you can ask for under UK law How to talk about your neurodivergence during applications & interviews By the end, you’ll have a clearer picture of where you might thrive in AI – & how to set yourself up for success.

AI Hiring Trends 2026: What to Watch Out For (For Job Seekers & Recruiters)

As we head into 2026, the AI hiring market in the UK is going through one of its biggest shake-ups yet. Economic conditions are still tight, some employers are cutting headcount, & AI itself is automating whole chunks of work. At the same time, demand for strong AI talent is still rising, salaries for in-demand skills remain high, & new roles are emerging around AI safety, governance & automation. Whether you are an AI job seeker planning your next move or a recruiter trying to build teams in a volatile market, understanding the key AI hiring trends for 2026 will help you stay ahead. This guide breaks down the most important trends to watch, what they mean in practice, & how to adapt – with practical actions for both candidates & hiring teams.