AI Architect & Delivery, VP at Morgan Stanley

Sandy, Utah, United States -

Full Time

Start Date

Immediate

Expiry Date

28 Jan, 26

Salary

0.0

Posted On

30 Oct, 25

Experience

10 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Automation, Leadership, Integration, Communication, Agile Methodologies, Software Development, Data Management, Natural Language Processing, Machine Learning, Robotic Process Automation, Project Management, Collaboration, Technical Solutions, Data Governance, AI System Design, DevOps Practices

Industry

Financial Services

Description

The candidate will work cross-functionally towards the goal of successful end-to-end delivery of Automation projects, bringing a willingness to do what it takes to get milestones delivered in a timely and accurate manner. This manager's position is responsible for overseeing the successful completion of several concurrent Automation projects. This role requires a combination of strategic and tactical problem solving, coupled with execution capability. The successful candidate will be a self-starter and have strong integration experience, with a proven track record of achieving success in a fast-paced, results-driven organization. This highly visible position involves interacting with a variety of individuals at all levels within the organization. Candidate must be driven, collaborative and a self-starter, be organized and detail-oriented, and have excellent communication skills. This position requires the ability to understand complex software and business concepts and to quickly absorb the business details. The Robotic Process Automation Manager: Lead a dynamic, multi-disciplinary team of developers, business analysts, testers, and support staff responsible for delivering high-quality automation solutions Ensure scalable, secure, and high-quality delivery through robust governance and disciplined execution. Is a strategic thinker who can balance long-term planning with day-to-day execution Provides a strong leadership presence with a collaborative style that promote empowerment, accountability and high performance Has strong business acumen with the ability to translate complex business requirements into scalable technical solutions Is skilled in identifying capability and process gaps, and setting clear direction to address them Act as a bridge between India based delivery teams and global leadership to ensure alignment and execution Builds a culture of performance, collaboration, and continuous learning. Monitor and analyze the effectiveness of Automation initiatives, providing regular reports to senior management. Manage project timelines, budgets, and resources to achieve department goals and objectives. Serves as a trusted subject matter expert to position best-practices with internal stakeholders. Stays current with new technology, products and enhancements, and their integration into application and operations. Builds strong relationships with internal business and technical teams to facilitate the development and delivery of automation requests. Ensures developed Automation solutions are delivered to the highest standards, inclusive of end-to-end testing are performed, meeting or exceeding expectations. Bachelor's or master's degree in the Computer Science, Software Engineering, Data Management, Business, Finance, Sciences, or equivalent education, training, and experience Minimum of 12+ years of experience in technology delivery with at least 5 years of experience in a leadership role. Proven experience overseeing large-scale software development function in a global delivery environment History of delivering transformation through automation, with measurable impact on operational efficiency and client satisfaction. Effective in stakeholder engagement at senior leadership levels with the ability to align technology delivery with business strategy Ability to develop and coach managers within the team to become strong, independent leaders capable of driving team performance and accountability. Ability to communicate effectively with senior leadership, business stakeholders, and technical teams across regions to ensure alignment and transparency. Ability to communicate complex technical concepts to non-technical stakeholders effectively. Ability to multi-task and reprioritize activities with little supervision. Experience with natural language processing (NLP), computer vision, and generative AI (LLMs, OpenAI APIs). Proven experience with Agile methodologies (e.g., Scrum, Kanban) and best practices, including application in technical leadership or project management roles. Strong background in software development, proficient in multiple programming languages and frameworks (e.g., Java, Python, C#, etc.), including advanced programming skills in Python (with AI/ML libraries), SQL, and Automation tools including the RPA tools. Deep understanding of structured governance, quality controls, and risk management in technology delivery, with a focus on data security and compliance for AI software development (including privacy-preserving ML such as differential privacy and federated learning). Proven experience with data migration and manipulation of large or ambiguous datasets, including advanced data engineering for AI (labeling, augmentation, and quality validation). Broad technical background with a solid grasp of AI system design and architecture, including integration of AI services/APIs (e.g., OpenAI). Hands-on expertise in developing, deploying, and maintaining machine learning models (supervised, unsupervised, reinforcement learning) at scale, using deep learning frameworks (TensorFlow, PyTorch, etc.). Proficient in model lifecycle management (experiment tracking, versioning, model serving) and AI/ML pipeline orchestration tools (MLflow, Kubeflow, Airflow, etc.). Knowledge of platforms like Dataiku, Tableau, Power BI, etc. Operational knowledge of Jira, Confluence, Salesforce. Knowledge of version control systems like Git, Bitbucket. Knowledge of DevOps practices and tools including CI/CD pipelines. Demonstrated leadership in building end-to-end AI products—from ideation and prototyping to production and maintenance. Knowledge of prompt engineering and custom fine-tuning of LLMs (e.g., GPT, Llama). Experience with vector databases for semantic search & RAG. Knowledge of graph neural networks, time series forecasting, or multimodal AI. Experience with data governance and model risk management in regulated environments. Our values - putting clients first, doing the right thing, leading with exceptional ideas, committing to diversity and inclusion, and giving back - aren't just beliefs, they guide the decisions we make every day to do what's best for our clients, communities and more than 80,000 employees in 1,200 offices across 42 countries. Our teams are relentless collaborators and creative thinkers, fueled by their diverse backgrounds and experiences. We are proud to support our employees and their families at every point along their work-life journey, offering some of the most attractive and comprehensive employee benefits and perks in the industry. There's also ample opportunity to move about the business for those who show passion and grit in their work. To learn more about our offices across the globe, please copy and paste https://www.morganstanley.com/about-us/global-offices into your browser. Consequently, our recruiting efforts reflect our desire to attract and retain the best and brightest from all talent pools. We want to be the first choice for prospective employees. It is the policy of the Firm to ensure equal employment opportunity without discrimination or harassment on the basis of race, color, religion, creed, age, sex, sex stereotype, gender, gender identity or expression, transgender, sexual orientation, national origin, citizenship, disability, marital and civil partnership/union status, pregnancy, veteran or military service status, genetic information, or any other characteristic protected by law.

Responsibilities

The candidate will oversee the successful completion of several concurrent Automation projects, ensuring high-quality delivery through robust governance and disciplined execution. They will lead a multi-disciplinary team and act as a bridge between delivery teams and global leadership to ensure alignment and execution.