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# Senior AI/ML Software Engineer

- **Company:** Insight Global
- **Location:** Bentonville, AR, United States
- **Experience:** Expert
- **Salary:** $122,720.0 - $153,920.0
- **Contract:** Permanent contract
- **Skills:** Java (Programming Language), Application Programming Interfaces (APIs), Artificial Intelligence, Microsoft Azure, Distributed Systems, Fault Tolerance, Java Web Services, Python (Programming Language), Machine Learning, OpenStack, Ansible, Tensorflow, Software Construction, Software Engineering, Pytorch, Large Language Models, Spring-boot, Software Application Programming, Generative AI, Backend, Build Management, Kubernetes, HuggingFace, Machine Learning Operations, Api Design, Restful APIs, Terraform, Software Version Control, Docker, Microservices
- **Published:** August 20, 2026
- **Apply:** https://jobs.insightglobal.com/jobs/find_a_job/arkansas/bentonville/senior-ai-ml-software-engineer/job-566476/

## About the Role

6-9+ years of software engineering experience
Strong background as a Java or Python backend developer
Expert-level experience with Java, Spring Boot, REST APIs, and microservices
Hands-on experience transitioning into AI/ML application development (libraries like Facebook profit and anomaly detection)
Experience integrating ML models into real production applications
Working experience deploying applications on OpenStack-based private cloud or similar enterprise platforms
Experience developing applications that run on Docker and Kubernetes (no platform ownership required)
Solid understanding of distributed systems, scalability, and service reliability

Nice to Have Skills & Experience

Experience with GenAI or LLM-based applications
Familiarity with MLOps concepts (model versioning, deployment patterns, monitoring)
Experience bridging Python-based ML workflows with Java services
Exposure to event-driven or data-intensive systems
Background in large enterprise environments with complex application ecosystems
Ansible, Terraform
Azure cloud
Prior Walmart Experience

## Description

Design and build AI-enabled backend services and APIs using Java and Python
Integrate machine learning and GenAI models into production software systems
Develop services that support model inference, orchestration, and business workflows
Collaborate with data scientists to productionize models built with TensorFlow, PyTorch, Hugging Face, or similar frameworks
Implement scalable, fault-tolerant microservices that consume and expose AI/ML capabilities
Deploy and run applications on OpenStack-hosted environments without owning underlying infrastructure
Work within containerized environments (Docker/Kubernetes) from an application perspective
Apply software engineering best practices around API design, performance, testing, and observability
Participate in architecture and design discussions for AI-driven systems
Troubleshoot and optimize application-level performance tied to data volume, model latency, and throughput


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