AI Architect & Delivery, VP en Morgan Stanley

Introducing Morgan Stanley at Work:

We know a lot about investing and are certain there’s no better investment a company can make than in its employees. People don’t just drive a company; they are the company. So when people work at their best, companies do too. Morgan Stanley at Work, a division of Morgan Stanley Wealth Management, provides workplace financial solutions that build employee financial confidence, foster loyalty and help our corporate clients attract and retain top talent. Our end-to-end offering spans Equity, Financial Wellness and Retirement Solutions. Plus, we provide all employees with Financial Empowerment, so they have the knowledge, tools and support needed to make the most of their workplace financial benefits.

What you’ll be part of – our Morgan Stanley at Work culture:

At Morgan Stanley at Work, we walk the talk. We have created a place for our employees to learn, achieve and grow – a place for people to build a career where you can thrive both personally and professionally. We are passionate about exceeding our clients’ expectations and helping them succeed. We are fearless in taking on new challenges that deliver exceptional results. We believe amazing things can happen when we work together in an environment where everybody has a true sense of belonging and their ideas are heard.

We value differences and are committed to providing a work environment where our people can do their best work. We look for people who are problem solvers, empathetic listeners, team players and inclusive leaders. We are committed to your growth and development, and your entire employee experience. We recognize that our people and culture are the keys to our success. We invite you to explore how you can be an integral part of our team.

AI Architect & Delivery Manager Key Responsibilities:

• AI Solution Architecture & Strategy
  • Define end-to-end architecture for AI solutions, encompassing data engineering, model development, deployment, governance, and monitoring.
  • Lead the selection, evaluation, and integration of AI technologies (including GenAI, ML, NLP, Computer Vision) and platforms to meet business requirements.
  • Drive AI strategy and roadmap in alignment with organizational objectives and business outcomes.
  • Design scalable, reliable, and secure AI systems that support automation and augmentation of enterprise processes.
• Delivery Management
  • Oversee full lifecycle delivery of complex AI and automation projects, from ideation and requirements through deployment and ongoing support.
  • Manage project plans, resource allocation, schedules, and budgets for multiple concurrent initiatives.
  • Establish and track KPIs, ensuring milestones are delivered on time and within scope.
  • Develop and maintain strong stakeholder relationships, facilitating effective communication and change management across cross-functional teams.
• Robotic Process Automation (RPA) Integration
  • Integrate AI models and capabilities with RPA platforms to enable intelligent automation and decisioning.
  • Identify automation opportunities leveraging AI to enhance existing RPA solutions and drive business value.
  • Ensure seamless interoperability between RPA bots and AI services.
• Technical Leadership & Team Enablement
  • Mentor and lead technical teams, fostering a collaborative, innovative, and high-performance culture.
  • Set best practices for AI/ML engineering and delivery, including MLOps, code quality, and model lifecycle management.
  • Provide technical guidance, code reviews, and architectural oversight to ensure robust and scalable solutions.
• Governance, Compliance, and Risk Management
  • Ensure AI systems adhere to enterprise security, compliance, and ethical standards, including data privacy and responsible AI principles.
  • Develop frameworks for model governance, versioning, monitoring, and auditability.
• Emerging Technologies & Thought Leadership
  • Stay abreast of advances in AI, automation, and related technologies; proactively identify opportunities for innovation.
  • Evangelize AI adoption within the organization through presentations, workshops, and knowledge sharing.
• Client Readiness & Support
  • Partner with client-facing teams to support onboarding, training, and enablement of AI-powered solutions.
  • Ensure clients are prepared for operational transformation enabled by AI and automation.

The AI Architect & Delivery Manager:

• Lead a dynamic, multi-disciplinary team of AI engineers, data scientists, automation specialists, business analysts, testers, and support staff to deliver innovative, high-quality AI and automation solutions including RPA solutions.
• Serve as a strategic thinker who balances long-term AI architecture and transformation planning with hands-on oversight of day-to-day solution delivery.
• Provide strong leadership with a collaborative style that fosters empowerment, accountability, and high performance across diverse technical and business teams.
• Demonstrate strong business acumen by translating complex business requirements into scalable, AI-driven solutions that drive measurable outcomes and operational efficiency.
• Innovate, develop, and implement strategies to integrate advanced AI technologies—including machine learning, generative AI, NLP, and computer vision—with Robotic Process Automation (RPA) to streamline and enhance Morgan Stanley at Work processes.
• Skillfully identify capability and process gaps within AI and automation delivery, setting clear direction and priorities to address them and drive continuous improvement.
• Act as a bridge between India-based AI delivery teams and global leadership, ensuring alignment of goals, technical standards, and execution across geographies.
• Build and nurture a culture of performance, collaboration, innovation, and continuous learning within the AI and automation team.
• Monitor, analyze, and report on the effectiveness and business impact of AI and automation initiatives, providing actionable insights to senior management.
• Manage project timelines, budgets, and resources to achieve departmental goals and support the successful delivery of AI and automation roadmaps.
• Serve as a trusted subject matter expert, positioning best practices for AI engineering, MLOps, and automation with internal stakeholders.
• Stay current with emerging AI technologies, methodologies, products, and enhancements, evaluating their potential for integration into enterprise systems and processes.
• Build strong relationships with internal business and technical teams to facilitate the development, adoption, and delivery of AI-powered automation solutions.
• Ensure all developed AI and automation solutions meet the highest standards for quality and performance, including rigorous end-to-end testing, validation, and compliance.

Qualifications & Experience

• 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. 
• Experience architecting and delivering large-scale AI and automation solutions in a complex enterprise environment.
• Hands-on expertise in machine learning, deep learning, GenAI, NLP, and RPA technologies.
• History of delivering transformation through automation, with measurable impact on operational efficiency and client satisfaction.
• Experience architecting and delivering large-scale AI and automation solutions in a complex enterprise environment.
• Hands-on expertise in machine learning, deep learning, GenAI, NLP, and RPA technologies.

Communication & Collaboration

• 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.
• Proven track record of stakeholder management across global teams, including effective handling of escalations, competing priorities, and delivery risks.
• Excellent planning and organizing skills. Can accurately scope out length and difficulty of tasks, sets objectives and goals, adjusts for problems and measures performance.
• Proven track record in successfully handling multiple projects at one time. Ability to multi-task and reprioritize activities with little supervision.

Strongly Desired Technical Qualifications

• 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.).
• Experience with natural language processing (NLP), computer vision, and generative AI (LLMs, OpenAI APIs).
• 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.

Preferred Technical qualification

• 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).

Preferred Skillsets

• 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.

While we thank all applicants for their interest, please note that only those individuals selected for an interview will be contacted.

Morgan Stanley's goal is to build and maintain a workforce that is diverse in experience and background but uniform in reflecting our standards of integrity and excellence. 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.

WHAT YOU CAN EXPECT FROM MORGAN STANLEY:

We are committed to maintaining the first-class service and high standard of excellence that have defined Morgan Stanley for over 89 years. 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. At Morgan Stanley, you’ll find an opportunity to work alongside the best and the brightest, in an environment where you are supported and empowered. 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.

Expected base pay rates for the role will be between $110,000 and $185,000 per year at the commencement of employment.  However, base pay if hired will be determined on an individualized basis and is only part of the total compensation package, which, depending on the position, may also include commission earnings, incentive compensation, discretionary  bonuses, other short and long-term incentive packages, and other Morgan Stanley sponsored benefit programs.

Morgan Stanley's goal is to build and maintain a workforce that is diverse in experience and background but uniform in reflecting our standards of integrity and excellence. 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.

Morgan Stanley is an equal opportunity employer committed to diversifying its workforce (M/F/Disability/Vet).