Noblesoft Solutions · 1 day ago
AI Lead Business Analyst (Hybrid in Tampa, FL)
St. Petersburg, FL
Contract
Hybrid
Lead/StaffNoblesoft Solutions is seeking an AI Lead Business Analyst to drive agentic AI initiatives within the banking and finance domain. The role involves leading business discovery, ensuring compliance with governance frameworks, and facilitating communication between technical and business teams.
Cloud ComputingCyber SecuritySoftware
No H1B
Hiring Manager
Anna George
Responsibilities
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
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
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
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
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
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
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
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
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
Qualification
Required
Must Have Banking or Finance Domain experience
Only USC/GC May Apply on W2
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
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
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
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
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
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
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
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
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
Company
Noblesoft Solutions
Noblesoft Solutions is a consulting firm that offers cyber security, cloud services, software and business intelligence services.
Founded in 2007
201-500 employees
Funding
Current Stage
Growth StageLeadership Team
Daniel McLinden
Vice President and Owner
Rakesh Reddy
President
Company data provided by crunchbase