Ashutosh Jha

Senior Software Engineer

Bengaluru, Karnataka, India9 yrs 5 mos experience

AI ML PractitionerAI Enabled

Key Highlights

Expertise in generative AI and backend engineering.
Developed Wally, an enterprise LLM-powered assistant.
Passionate about pushing AI boundaries and innovative solutions.

Stackforce AI infers this person is a Backend-heavy Fullstack engineer specializing in SaaS and generative AI solutions.

Contact

ashutosh.jha@walmart.com LinkedIn

Skills

Core Skills

Large Language Models (llm)Retrieval-augmented Generation (rag)Backend DevelopmentCode Modernization

Other Skills

Apache KafkaCC (Programming Language)C++CI/CDCascading Style Sheets (CSS)Continuous Integration and Continuous Delivery (CI/CD)GenAIGo (Programming Language)Google Cloud Platform (GCP)HTMLHigh-Level DesignIntegrationJavaJavaScript

About

Walmart has benefited from expertise in generative AI and advanced backend engineering, delivering solutions like Wally, an AI assistant leveraging Retrieval-Augmented Generation (RAG) and the ReAct paradigm. The team successfully implemented semantic query translation and an evaluation framework for AI response accuracy. Contributions have also included enhancing event-driven architectures for efficient LLM usage and refining dashboard functionalities for data-driven insights. With over eight years of experience across Walmart and McAfee, the focus has been on scalable backend systems, distributed microservices, and modernizing legacy codebases. A passion for pushing AI boundaries and collaborating on cutting-edge technologies defines the mission to empower organizations through innovative and reliable engineering solutions.

Experience

9 yrs 5 mos

Total Experience

4 yrs 11 mos

Average Tenure

4 yrs 6 mos

Current Experience

Walmart

2 roles

Senior Software Engineer

Promoted

Nov 2025 – Present · 7 mos

GenAI Chat Platform (Wally)
Driving architecture and development of Wally, an enterprise LLM-powered conversational assistant for internal analytics use-cases (sales, revenue, inventory, CX insights, etc.). Worked on the migration from LangChain to LangGraph, implementing checkpointing and episodic memory for stateful orchestration and improved context retention. Optimized token-window usage, built chat personalization capabilities, and integrated secure token-based authentication through the gateway.
Designed multi-agent workflows including Agent-to-Agent (A2A) integrations, and implemented MCP-based client–server tooling, enabling centralized tool registries with structured prompts and metadata. Developed ReAct-driven decision nodes in LangGraph for tool selection, execution, and looped reasoning using GPT-4o and GPT-5. In addition, contributed to CI/CD, deployment, cross-team integrations, and production reliability.

Retrieval-Augmented Generation (RAG)ReActContinuous Integration and Continuous Delivery (CI/CD)Large Language Models (LLM)GenAI

Software Development Engineer

Dec 2021 – Nov 2025 · 3 yrs 11 mos

Key Responsibilities:
1. LLM & GenAI Solutions: Working on development of Wally, an AI assistant using the ReAct paradigm to dynamically translate user queries into tool-specific actions. Designed and implemented a full Retrieval-Augmented Generation (RAG) pipeline for knowledge agents, semantic query translation with LLMs, and an evaluation layer leveraging chain-of-thought reasoning to score responses against golden standards.
2. Event-Driven Architecture:
Developed GURU GenAI Async services, leveraging bidirectional service channels for synchronous transactions, error handling, and efficient use of large language models (LLMs) through Walmart Gateway.
3. Dashboard Enhancements:
Improved the Fusion Dashboard, introducing user-friendly designs and smart narratives for better analytics, integrating LLMs for insights.
4. API Development:
Created a new API endpoint for Sam’s SRE Gate from scratch, enabling better dependency calculations and violation checks on GitHub pull requests.
5. CI/CD Implementation:
Set up CI/CD pipelines, ensuring secure integration of secrets using Akeyless, and developed Docker images for application deployment.
6. Cloud Solutions:
Built scheduled comparator jobs over Google Cloud Platform (GCP) and monitored GCP pipelines and dashboards (Grafana, Splunk, Azure).
7. Distributed Systems Development: Developed score catalog asset projects and taxonomy microservices for parallel data processing, storage, and providing REST APIs to consumers.
Key Achievements:
1. Accelerated GenAI job processing with Redis and parallel execution optimizations.
2. Optimized Job Processing:
Enhanced job processing speed using Redis, Parallel processing for GURU GenAI Async services.
3. Smart Analytics Integration:
Delivered insightful analytics through smart narratives using GenAI models.
4. Improved Dependency Management:
Enhanced GitHub pull request processes with an API for Sam's SRE Gate.

Retrieval-Augmented Generation (RAG)ReActContinuous Integration and Continuous Delivery (CI/CD)Google Cloud Platform (GCP)MicroservicesLarge Language Models (LLM)

Mcafee

2 roles

Software Engineer

Jun 2017 – Dec 2021 · 4 yrs 6 mos · Bengaluru, Karnataka, India

Key Responsibilities:
1. ePolicy Orchestrator (ePO) Development:
Contributed to the ePO project, focusing on both backend and frontend development to manage large-scale deployments effectively.
2. Code Modernization:
Revised and modularized legacy codebases to meet modern development standards, improving functionality and reducing operational costs.
3. Integration:
Collaborated with various teams to integrate extensions and enhance system interoperability.
4. Bug Resolution and Feature Enhancement:
Proactively identified and resolved bugs while incorporating new features to optimize performance.
5. Client Collaboration:
Conducted needs analysis with customers, defined requirements, and developed clear specifications for project plans.
6. Testing and Quality Assurance:
Conducted thorough testing of new features and implemented corrections to ensure high-quality software releases.
Key Achievements:
1. Optimized Large-Scale Deployments:
Orchestrated efficient software rollouts for enterprise clients, ensuring smooth deployment processes.
2. Improved Code Efficiency:
Successfully modernized outdated codebases, reducing technical debt and improving maintainability.
3. Enhanced Customer Satisfaction:
Delivered solutions aligned with client needs, earning recognition for addressing issues promptly and effectively.
4. Cross-Team Collaboration:
Played a vital role in integrating extensions and ensuring seamless communication between various teams.