Spec-business Intelligence

Verizon Verizon · Telecom · Hyderabad, India +1

This role focuses on building and implementing AI solutions within a Financial Planning & Analysis (FP&A) organization. The primary goal is to automate and enhance financial processes using AI, including architecting intelligent workflows, creating AI-enhanced data storytelling, and utilizing generative AI tools for financial analysis and reporting. The role involves bridging finance and technology teams, working with LLM APIs, and owning the developer experience of agentic interactions for finance end-users. It emphasizes building AI agents or agentic systems in production and understanding LLM capabilities.

What you'd actually do

  1. Identify bottlenecks in traditional FP&A processes (like month-end close or manual data consolidation) and spearhead the implementation of automations and AI solutions.
  2. Transform complex, multi-layered datasets into clear, actionable intelligence using advanced data visualization tools and AI-generated insights.
  3. Act as the crucial link between traditional FP&A and data science teams, ensuring AI algorithms are trained with deep financial context and commercial acumen
  4. Utilize generative AI tools to rapidly synthesize financial data, draft preliminary variance narratives, and accelerate the reporting cycle.
  5. Design and build AI solutions that interact with development tools, codebases, and team workflows in meaningful ways.

Skills

Required

  • Bachelor’s degree and Four or more years of work experience in financial report automations.
  • Five or more years of relevant work experience in Business Intelligence/Analytics within FP&A teams (but not limited to this function).
  • Deep, hands-on experience building AI agents or agentic systems in production.
  • Strong understanding of LLM capabilities and limitations across multiple models (Claude, Gemini,

Nice to have

  • Experience with Qlik/ Looker Applications
  • Experience with LLM APIs (Claude, Gemini, Codex, and others)

What the JD emphasized

  • Deep, hands-on experience building AI agents or agentic systems in production.
  • Strong understanding of LLM capabilities and limitations across multiple models (Claude, Gemini,

Other signals

  • AI-driven FP&A
  • intelligent workflows
  • AI-enhanced data storytelling
  • Prompt Engineering for Finance
  • AI agents or agentic systems in production
  • LLM APIs