AVP, GenAI & Strategic Intelligence Architect

711 MS Smith Barney, LLC

Alpharetta (GA)

On-site

USD 120,000 - 180,000

Full time

14 days+

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Job summary

Morgan Stanley is seeking an AVP-level technical analyst/developer to drive Generative AI enablement within the Agility & Strategic Intelligence team. You will translate business needs into functional specs, design API-based solutions, and coordinate cross-team efforts to scale AI capabilities across the firm.

You will lead technical delivery, mentor analysts, and ensure data quality and compliance while collaborating with stakeholders and vendors.

Qualifications

Bachelor’s or Master’s degree in Computer Science, Software Engineering, Business, Finance, Sciences, or equivalent education, training, and experience.
6+ years of progressive experience in software development, data integration, technical analysis, and/or solution delivery, with proficiency in multiple programming languages and a strong preferred focus on Python.
3+ years of technical leadership experience with the ability to lead, mentor, and coordinate developers/analysts to deliver high-quality solutions.
Strong background in requirements gathering and analysis, with the ability to produce functional requirements, user stories, acceptance criteria, technical specifications, data mapping, controls, and interface/ETL requirements.

Responsibilities

Serve as an AVP-level technical analyst/developer within the Agility & Strategic Intelligence team supporting Morgan Stanley at Work, with primary focus on Generative AI enablement, AI platform adoption, and related data/integration tooling.
Partner with business stakeholders to gather, analyze, and document requirements, translating them into high-quality functional and technical specifications, user stories, process flows, data mappings, controls, and test scenarios.
Support the delivery of reusable AI capabilities and platform-aligned solutions that accelerate high-value GenAI use cases across the firm.
Design and build technical solutions based on requirements, including APIs/services, data transformation, workflow improvements, retrieval patterns, and automation enablement where appropriate.
Support and enhance existing tool-based workflows and AI-enabled solutions, including troubleshooting, coordinating fixes across teams and vendors, and strengthening data quality and control outcomes.