Distinguished Data Scientist, Agentic AI Systems Engineering & Model Post-Training

Walmart

Confirmed live yesterday High trust

Quick summary

Work type
On-site
Location
Bentonville, AR
Salary
$130,000–$260,000 / yr
Employment
Full-time
Posted
56 days ago
Freshness
Confirmed live yesterday
Nearby
99+ roles within 25 mi

Market check

Salary context

Competitive pay

How this pay compares to similar roles

Similar $203k
This role $195k
$114k $276k
below market most similar roles pay here above market

This role pays less than 52% of similar roles. Most pay $162,000–$244,537 — the blue band above. At the midpoint, this role pays about $195k versus about $203k for comparable roles.

Based on 240 similar postings.

Employer

About Walmart

Walmart Inc. is the world''s largest retailer by revenue, operating a chain of hypermarkets, discount department stores, and grocery stores, as well as a growing e-commerce presence through Walmart.com. Industry: General Merchandise & Grocery Retail

Walmart currently has 743 open roles on FindRole.

Listed pay typically runs $117,000–$234,000 across 541 roles with salary data.

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View all roles at Walmart

At a glance

TL;DR · Distinguished Data Scientist, Agentic AI Systems Engineering & Model Post-Training

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JOB TITLE: (USA) Distinguished, Data Scientist - Agentic AI Systems Engineering & Model Post-Training The Supply Chain AI Lab & Innovation Factory is seeking a Distinguished technical leader to build production-grade agentic AI systems. You will own the end-to-end architecture, implementation, and operation of autonomous multi-agent applications designed to solve complex supply chain problems, specifically the Autonomous Supply Chain Engine. Your daily work involves building agent runtimes, backend services, APIs, and React/TypeScript interfaces. You will utilize frameworks like Pydantic AI, LangGraph, LangChain, AutoGen, and LlamaIndex to create systems capable of long-horizon planning and tool use. Additionally, you will perform model post-training using RLHF, RLAIF, and supervised fine-tuning to improve reasoning. Key technologies include Python, Go, Java, Kafka, Flink, Spark, and Google Cloud Platform to ensure scalable, secure, and auditable enterprise AI operations.

What does a Data Scientist earn?

Median $173200 from 328 postings across 57 companies.

See salary data

Skills

Python Go TypeScript React Pydantic AI LangGraph LangChain AutoGen LlamaIndex Google Cloud Platform Kafka Flink Spark OpenTelemetry Grafana Kubernetes Docker CI/CD RLHF RLAIF TensorFlow scikit learn Graph Databases Model Context Protocol WCAG 2.2 AA

What you'll do

  • Build and own end-to-end production systems for autonomous multi-agent applications.
  • Design and implement agent runtimes, orchestration layers, and execution models using frameworks like LangGraph or Pydantic AI.
  • Develop full-stack components including backend APIs, database schemas, and React/TypeScript user interfaces.
  • Engineer governed knowledge infrastructure using vector retrieval, knowledge graphs, and temporal models.
  • Implement policy-first control planes for secure tool access, identity authorization, and auditable human approvals.
  • Improve model reasoning through hands-on post-training techniques like RLHF, SFT, and distillation.
  • Establish AgentOps practices for tracing, evaluation, cost controls, and continuous improvement of long-running systems.
  • Set multi-year technical direction and mentor senior engineering teams on agentic AI architecture.

What we're looking for

  • Must have 10+ years of hands-on software engineering and architecture experience.
  • Must have a Master's degree in a related field with 4 years of experience, or 8 years of experience in a related field.
  • Must have a Bachelor's degree in a related field with 6 years of experience in an analytics related field.
  • Must possess expert Python skills and strong production backend capability in Go, Java, or TypeScript.
  • Must have deep experience in agentic AI engineering, including multi-agent systems, RAG, and model post-training (RLHF, SFT, distillation).
  • Must have deep production experience with distributed systems, Kubernetes/Docker, CI/CD, and telemetry/observability tools.
  • Must have full-stack capability across React/TypeScript frontends, APIs, and data layer design.
  • Ph.D. in a related field is preferred.

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