Your Opportunity

We are looking for an exceptionally skilled, hands-on, and innovation-minded AI Scientist & Engineer to bridge the gap between advanced data science, experimental machine learning, and scalable enterprise software engineering in our new Assurance Innovation Lab.

The Assurance Innovation Lab (ASR Labs) serves as the experimentation, innovation, and solution development engine supporting our practice. Working alongside other functions nationally - including our Innovation Operations, AI Studio - Central Lab, Central Data Team, and Innovation & Change (I&C) - you will help ideate, design, prototype, develop, and deliver scalable solutions that modernize how work gets done across our Assurance practice.

In this net new role, you will work with a team dedicated to building modern applications, intelligent workflow solutions, integrations, and AI-enabled platforms that support business transformation and operational modernization initiatives across our practice. You will be reporting to our Head of ASR Transformation, and have a dotted line to our technically astute managers in our AI Studio - Central Lab.

This hybrid role is responsible for extracting high-value insights from complex datasets, training custom large language models (LLMs), and designing, building, and deploying production-grade agentic workflows and retrieval-augmented generation (RAG) solutions. Operating under enterprise governance frameworks like ISO/IEC 42001 and the NIST AI Risk Management Framework (AI RMF), you will deliver responsible, scalable, and highly impactful AI systems that drive true business transformation.

The ideal candidate for this role will have 3-5 years of hands-on experience building, fine-tuning, deploying, and monitoring machine learning models and Generative AI solutions in an enterprise production environment. This role rests on the ability to work cross-functionally with AI Architects, AI Studio Leads, ML Engineers, Data Scientists, Full Stack Developers, and citizen developers on firm-wide strategic initiatives.

Key Responsibilities:

AI, Machine Learning & Advanced Analytics

• Design, build, train, and optimize machine learning and AI models to support Assurance transformation initiatives
• Develop intelligent solutions leveraging NLP, generative AI, knowledge graphs, predictive analytics, and automation capabilities
• Support experimentation and prototyping of emerging AI technologies and use cases within Assurance
• Evaluate model performance, explainability, reliability, and responsible AI considerations
• Contribute to development of scalable AI-enabled workflows and intelligent operational solutions

Cross-Functional Collaboration & Business Partnership

• Partner closely with Transformation Relationship Managers (TRMs), Assurance practitioners, Innovation & Change (I&C), Data & Analytics, and leadership teams
• Contribute to multidisciplinary teams focused on solving business problems through technology, AI, automation, and workflow redesign
• Support rapid experimentation, prototyping, and scaling of innovative solutions within the Assurance R&D Lab
• Help bridge strategy, business operations, and technical execution to accelerate transformation outcomes
• Translate complex business problems into practical analytical and AI-driven solutions
• Participate in discovery sessions, design thinking workshops, ideation activities, and working groups

Data Engineering & Platform Enablement

• Collect, clean, transform, and analyze large and complex datasets from multiple sources
• Build and maintain scalable data pipelines and model integration frameworks
• Support connected data and intelligence capabilities aligned to the broader Total Assurance Ecosystem strategy
• Work with cloud-based environments and modern AI infrastructure to support scalable deployment and operationalization
• Collaborate with engineering teams to productionize and operationalize solutions

Innovation & R&D Collaboration

• Work closely with the Assurance R&D Lab to validate concepts, prototype solutions, and scale successful initiatives
• Stay informed on emerging trends across AI, automation, Assurance technology, data science, and intelligent systems
• Help evaluate external tools, platforms, and ecosystem opportunities relevant to Assurance Transformation
• Contribute to a culture of experimentation, innovation, and continuous improvement

Requirements

• Programming Languages: Expert-level Python is required. Professional proficiency in R, Scala, Java, or TypeScript is highly desirable
• AI & LLM Frameworks: Deep experience with OpenAI API, Anthropic, Hugging Face, LangChain, LlamaIndex, and LangGraph
• Data Science & Deep Learning: Comprehensive experience with PyTorch, TensorFlow, Scikit-Learn, Pandas, NumPy, and Matplotlib
• Model Training: Practical knowledge of training and fine-tuning open-source LLMs/transformers (e.g., Llama, Mistral) and implementing Knowledge Graphs
• Data & Vector Infrastructure: Hands-on experience with Pinecone, Milvus, Weaviate, and standard SQL/NoSQL databases
• DevOps / MLOps: Advanced proficiency with Docker, Kubernetes, Nvidia Triton Inference Server, and MLOps tracking platforms (MLflow, Weights & Biases)
• Cloud Platforms: Strong working knowledge of enterprise cloud environments including Microsoft Azure (Azure AI / AI Foundry), AWS (Bedrock), or GCP
• Architecture & Patterns: Demonstrated mastery of Retrieval-Augmented Generation (RAG) architectures and multi-Agent AI design patterns

The expected range of compensation for this role is $110,000 to $160,000 annually.

Ideal Candidate Will Have

• A systematic approach to problem-solving and devising practical solutions for complex enterprise bottlenecks
• Published academic research in top-tier ML/AI conferences/journals OR demonstrated practical excellence through Kaggle competitions
• High passion for translating complex data and multi-agent system capabilities into tangible, actionable business value
• Strong business curiosity and problem-solving mindset
• Passion for applying AI and data science to practical operational challenges
• Ability to balance experimentation with scalable execution
• Strong collaboration and stakeholder engagement skills
• Interest in workflow modernization, intelligent automation, and future-state operating models
• Passion for continuous learning and emerging technologies

Why Join the Assurance Innovation Lab?

This is an opportunity to help build the future of Assurance through modern platforms, intelligent workflows, and scalable AI-enabled solutions.

You will join a high-performing team to work on high-impact transformation initiatives that directly influence how the business operates and delivers value.

The role offers exposure to:

• Enterprise transformation and innovation programs
• AI-enabled applications and intelligent workflow solutions
• Modern cloud and engineering ecosystems
• Cross-functional collaboration with Assurance, AI-Studio, Data & Analytics, Innovation & Change, and leadership teams
• Rapid experimentation and enterprise-scale delivery initiatives
• Most importantly, you will help create practical solutions that improve how work gets done across our Assurance practice