Lead Business Analyst(Gen AI/AI/LLM)- Only W2 and Locals for Hybrid work!

US Citizens and Green card holders would be considered only W2 for hybrid work.

NOTES from hiring manager:

role is for local candidates only to work onsite hybrid model min 2 days per week in St Pete at RJF, no fully remote options role has a chance to convert to FTE assuming performance and future budgets project.

work is focused on Agentic AI platform and Machine Learning initiatives

The BA is more of a true Lead Functional BA but any technical skills are a value add

This group does 2 week sprints, need corporate polish with excellent comm skills

Duties:

Strategic Analysis and Solution Definition

1. Lead business discovery for agentic AI initiatives, translating enterprise objectives into clearly defined product and system requirements.
2. Partner with engineering, data science, and risk teams to ensure each solution aligns with firm priorities, compliance standards, and long-term AI governance frameworks.
3. Define success metrics and measurable outcomes for agentic systems that drive advisor productivity, client intelligence, and firm efficiency.

Requirements Management

1. Elicit, document, and refine requirements that span AI reasoning, data integration, knowledge orchestration, and adaptive decision flows.
2. Bridge technical and business contexts — ensuring that the intent, capabilities, and constraints of frameworks such as Strands, CrewAI, LangGraph, and Agent Core are accurately reflected in user stories and acceptance criteria.
3. Manage change control for rapidly evolving agentic capabilities, balancing agility with traceability and compliance.

Stakeholder Alignment and Communication

1. Act as the primary interface between business leaders, developers, and governance teams to maintain a shared understanding of priorities, tradeoffs, and dependencies.
2. Translate complex AI and engineering concepts into concise, business-relevant narratives for executives and non-technical audiences.
3. Facilitate workshops, design reviews, and model demonstrations to ensure feedback loops are fast and informed.

Governance and Risk Integration

1. Partner with Compliance, Data Governance, and Enterprise Architecture to embed ethical, auditable, and transparent AI operations throughout solution design.
2. Ensure agentic AI initiatives align with data residency, privacy, and supervisory regulations applicable to financial services.

Operational Excellence and Delivery

1. Drive the full delivery lifecycle — from concept through deployment — maintaining clear documentation, prioritization, and validation processes.
2. Support testing, model validation, and release readiness activities by providing context, user scenarios, and performance benchmarks.
3. Continuously refine business processes and operating models to leverage the adaptive nature of agentic systems.

Skills

Technical and Analytical Proficiency

1. Strong understanding of AI/ML concepts, particularly agentic and LLM-based architectures.
2. Familiarity with AWS cloud environments, data pipelines, and API-driven ecosystems.
3. Ability to interpret and validate outputs from frameworks such as Strands, CrewAI, LangGraph, and Agent Core in collaboration with engineers.
4. Experience working with structured and unstructured data, embeddings, and retrieval systems to support intelligent automation.

Business and Strategic Insight

1. Deep expertise in requirements analysis, process optimization, and value mapping across enterprise systems.
2. Strong ability to quantify business impact, model ROI, and articulate how AI systems drive competitive advantage.
3. Understanding of financial services operations, risk management, and compliance implications in production AI environments.

Leadership and Collaboration

1. Proven success leading multi-disciplinary teams across data, engineering, and governance functions.
2. Skilled in translating ambiguity into structure and clarity; comfortable operating at the intersection of innovation and regulation.
3. Exceptional written and verbal communicator capable of aligning senior stakeholders around transformative AI initiatives.

Mindset and Behavior

1. Analytical precision, bias for execution, and intellectual curiosity about AI’s evolving role in business decision-making.
2. Integrity-driven; consistently aligns actions with client outcomes and firm values.
3. Embraces iterative learning and continuous improvement in both systems and self.

Education

Bachelor’s degree in Information Systems, Computer Science, a related field or equivalent experience.

5 years of experience in business analysis, product ownership, or AI/technology-driven transformation—ideally within financial services or a regulated enterprise.