(ind) Staff, Solution Consultant

Walmart · Retail · Bangalore, KA, India

This role involves building and deploying AI-powered agents to automate Finance processes within Walmart. The focus is on hands-on execution, translating documented Finance processes into executable agent workflows, and implementing agent logic using tools like Copilot and Code Puppy. It requires understanding Finance rules, configuring agent orchestration, and ensuring agents operate reliably in production.

What you'd actually do

  1. Build Finance-focused AI agents using Copilot, Code Puppy, and agentic AI platforms
  2. Translate documented Finance processes into executable agent workflows
  3. Implement agent logic to interpret inputs, apply Finance rules, and execute tasks
  4. Configure agent orchestration, tool usage, and decision logic
  5. Understand assigned Finance processes and execution steps in depth

Skills

Required

  • 13–15 years of experience in Finance operations, transformation, or systems execution roles
  • Strong hands-on knowledge of core Finance processes (R2R, P2P, O2C, FP&A, Controls)
  • Demonstrated ability to build and execute solutions, not just design them
  • Comfort working with AI tools, low-code/pro-code platforms, and automation frameworks
  • Strong logical thinking and attention to detail
  • Clear communication skills with Finance and technical teams

Nice to have

  • Hands-on experience building AI agents using Copilot, Code Puppy, or similar tools
  • Exposure to agentic AI workflows, prompt engineering, and orchestration
  • Experience deploying AI or automation in large enterprise Finance environments
  • Understanding of Finance controls, audit, and compliance requirements

What the JD emphasized

  • execution-focused
  • hands-on
  • building working agentic solutions
  • not be responsible for discovery, prioritization, or ideation
  • impact comes from understanding defined Finance processes and executing high-quality AI agent builds that operate reliably in production environments
  • emphasizes execution, simplification, automation, and scale
  • Hands-On Build, Test, and Iterate
  • Actively build, test, and refine agents during execution cycles
  • Apply agentic AI concepts such as task decomposition and orchestration
  • Combine LLM reasoning with deterministic Finance logic
  • Implement grounding, guardrails, and structured prompting
  • Strong hands-on knowledge of core Finance processes
  • Demonstrated ability to build and execute solutions, not just design them
  • Hands-on experience building AI agents using Copilot, Code Puppy, or similar tools
  • Exposure to agentic AI workflows, prompt engineering, and orchestration

Other signals

  • AI-powered agents
  • automate Finance processes
  • agentic AI frameworks
  • production-ready AI agents
  • agent orchestration
  • tool usage
  • decision logic
  • LLM reasoning
  • guardrails