Lead Business Analyst (AI)

This role is only open to USC/GC holders who can work on our w2.

No C-C is possible

There will be a F2F interview

Job Title: Lead Business Analyst

Location: St. Petersburg, FL (Hybrid)

Duration: Long term contract

Duties

Strategic Analysis and Solution Definition

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

Requirements Management

• Elicit, document, and refine requirements that span AI reasoning, data integration, knowledge orchestration, and adaptive decision flows.
• 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.
• Manage change control for rapidly evolving agentic capabilities, balancing agility with traceability and compliance.

Stakeholder Alignment and Communication

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

Governance and Risk Integration

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

Operational Excellence and Delivery

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

Skills

Technical and Analytical Proficiency

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

Business and Strategic Insight

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

Leadership and Collaboration

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

Mindset and Behavior

• Analytical precision, bias for execution, and intellectual curiosity about AI’s evolving role in business decision-making.
• Integrity-driven; consistently aligns actions with client outcomes and firm values.
• 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.