Business Analyst - BIZANT

Location: NY
Job: Hybrid (3-4 days in office)
Max vendor Rate: ####/hr
Duration: 6 Months

Job title: Front Office Applied AI Engineer Global Markets Distribution

We are seeking a highly entrepreneurial Front Office Applied AI Engineer to sit directly with our Equities and Fixed Income Sales teams and transform how Sales operates through AI, automation, analytics, and workflow innovation.
This is not a strategy role or a back-office technology role.
We are looking for a builder who can work directly with salespeople, identify opportunities, rapidly prototype solutions, deploy them into production, and continuously improve them based on user feedback.
The successful candidate will develop AI agents, copilots, CRM workflows, analytics applications, and productivity tools that improve client engagement, sales effectiveness, cross-sell opportunities, and management insight.

Key Responsibilities:

Build AI Solutions for Sales
Design and deploy AI agents, copilots, and workflow automations for Equities and Fixed Income Sales.
Build additional tools that help salespeople prepare for meetings, prioritize clients, identify opportunities, distribute research, and generate market commentary.
Create reusable prompt libraries, agent frameworks, and workflow templates.
Develop next-best-action, client prioritization, and cross-sell recommendation capabilities.
Deliver Commercial Analytics
Build additional dashboards and analytics tools for Sales, Management, and COO teams.
Develop revenue, wallet share, market share, pipeline, client activity, and coverage analytics.
Integrate CRM, research, holdings, market activity, and sales data into actionable insights.
Automate recurring reporting and management information workflows.
Engineer for Production
Design and build production-grade applications, APIs, workflows, and data products.
Apply modern software engineering practices including testing, source control, CI/CD, monitoring, documentation, and release management.
Partner with Technology, Data, Compliance, and Risk teams to deploy scalable and supportable solutions.
Build Responsible AI
Implement evaluation and monitoring frameworks for AI applications.
Measure and improve quality, accuracy, hallucination risk, latency, cost, adoption, and user feedback.
Ensure solutions are controlled, auditable, permissioned, and compliant.
Build AI workflows that respect data entitlements, access controls, and governance requirements.

Must Have Skills:

Applied AI & Engineering
Expert Python and strong SQL skills.
Experience building production AI applications and agent-based workflows.
Experience with LLMs, prompt engineering, RAG, semantic search, vector databases, and agentic frameworks.
Familiarity with Azure OpenAI, Copilot Studio, Semantic Kernel, LangChain, CrewAI, AutoGen, or similar technologies.
Experience with APIs, workflow orchestration, data pipelines, and enterprise integrations.
Understanding of LLMOps, model evaluation, observability, monitoring, testing, and AI governance.
Cloud & Platform Engineering
Experience deploying applications on enterprise cloud platforms.
Understanding of DevOps, CI/CD, containerization, identity management, monitoring, and access controls.
Ability to build solutions that scale beyond prototype environments.
Data Governance
Experience working with sensitive business data in controlled environments.
Understanding of entitlements, information barriers, auditability, and permissioning.
Ability to build AI solutions grounded in approved and governed data sources.
Commercial & Front Office Knowledge
Strong understanding of institutional sales workflows and client coverage models.
Familiarity with CRM workflows, client prioritization, research distribution, market commentary, and sales productivity tools.
Understanding of revenue attribution, wallet share, market share, pipeline management, and client analytics.
Working knowledge of Equities, Fixed Income, Credit, Rates, FX, Financing, or related capital markets businesses.
Ability to engage credibly with Sales, Trading, Research, COO, Technology, and Compliance stakeholders.
Sitting beside a salesperson discussing client coverage challenges.
Building AI agents and workflows in Python.
Writing complex SQL and data pipelines.
Designing dashboards and analytics.
Integrating enterprise systems and APIs.
Monitoring and improving AI performance in production.
Explaining technical concepts to senior business leaders.
Taking a solution from idea to production deployment.
You thrive in ambiguity, move quickly, and care deeply about building products that people actually use.

Success in the Role
You will have:
Delivered multiple AI agents and workflow automations used daily by Sales.
Reduced manual administrative workload across coverage teams.
Improved CRM discipline, client prioritization, and sales productivity.
Enhanced cross-sell identification and meeting preparation.
Improved management reporting and commercial analytics.
Established scalable AI engineering, governance, and LLMOps practices across Global Markets Distribution.
Helped build one of the industry's most technology-enabled institutional sales organizations.