WA

Senior Solution Consultant 1

Walmart
Bangalore5-9 LPA Posted 30 Apr 2026
FULL TIME
Machine Learning
Artificial Intelligence

Job Description

Key Responsibilities

AI Solution Architecture & Technical Leadership

  • Provide end-to-end technical leadership for AI/LLM-based Finance solutions.
  • Design scalable, secure, and governed AI architectures aligned with enterprise standards.
  • Translate Finance business requirements into AI-driven solution designs and technical specifications.
  • Review solution architecture and ensure compliance with responsible AI and governance frameworks.
  • Guide development of intelligent assistants and conversational AI systems for Finance users.

GenAI / LLM Engineering & Innovation

  • Drive adoption of modern AI patterns including Retrieval Augmented Generation (RAG) and Model Context Protocol (MCP).
  • Lead design of natural language interfaces and AI-powered automation systems.
  • Evaluate emerging AI tools, frameworks, and platforms for enterprise Finance use cases.
  • Improve accuracy, grounding, and reliability of LLM-generated outputs.

Hands-on Technical Contribution

  • Debug and optimize AI models, prompts, and system outputs.
  • Work with large-scale datasets to improve AI performance and data quality.
  • Validate end-to-end AI system behavior and performance.
  • Support integration of AI systems with BI and analytics platforms.
  • Enhance SQL-based validation, data analysis, and optimization processes.

Stakeholder & Cross-functional Collaboration

  • Communicate AI concepts clearly to non-technical Finance stakeholders.
  • Partner with Finance, Data Science, and Engineering teams to define AI opportunities.
  • Influence adoption of AI-driven workflows across Finance operations.
  • Promote responsible AI practices and AI literacy across teams.

AI Governance & Quality Assurance

  • Ensure AI solutions meet enterprise standards for quality, security, and compliance.
  • Support AI lifecycle governance including model evaluation and performance tracking.
  • Drive continuous improvement in AI solution reliability and usability.

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