AI Solutions Engineer (Python, DevOps, Cloud, LLM)

NTT DATA • Dallas, TX

7d

About The Position

Platform Installation & Engineering Install, validate, and operate platform components using modern DevOps practices (Kubernetes, Helm, Git-based deployments). Validate network connectivity, security configurations, logging, and monitoring. Manage versioned deployments, upgrades, and rollback procedures using Git-driven release workflows. Test end-to-end platform functionality using representative repositories and workloads. Operate and maintain monitoring, logging, and alerting to ensure platform health post-deployment. Guide teams on repository hygiene, modularization, access controls, and branching strategies. Troubleshoot ingestion, analysis, and runtime issues across code, infrastructure, and integrations. Provide architectural guidance and clearly communicate trade-offs when preparing systems for AI-driven workflows. Work directly with customer engineers to drive adoption and unblock progress.

Requirements

• Bachelor's degree in Computer Science, Information Technology, or a related field, or equivalent practical experience.
• 2+ years of experience in a technical implementation or solutions engineering role, preferably with a SaaS product.
• 2+ years of experience with Azure, OpenAI, and other cloud and LLM providers
• 7+ years strong in software development lifecycle (SDLC) practices and common source control workflows (e.g. Git branching strategies, pull requests, release versioning).
• 2+ years Machine Learning and Deep Learning Expertise
• 5+ years of strong understanding of software integration principles and APIs.
• 5+ years Programming proficiency in Python, R, and Java
• Ability to travel to client sites as needed
• Ability to provide architectural guidance and communicate trade-offs when preparing code for analysis workflows.
• Comfortable reading code at a structural level, with proficiency in at least one code language.
• Excellent problem-solving and analytical skills.
• Exceptional communication and interpersonal skills, with the ability to explain complex technical concepts to non-technical audiences.
• Proven ability to manage multiple projects simultaneously and prioritize effectively.

Responsibilities

• Install, validate, and operate platform components using modern DevOps practices (Kubernetes, Helm, Git-based deployments).
• Validate network connectivity, security configurations, logging, and monitoring.
• Manage versioned deployments, upgrades, and rollback procedures using Git-driven release workflows.
• Test end-to-end platform functionality using representative repositories and workloads.
• Operate and maintain monitoring, logging, and alerting to ensure platform health post-deployment.
• Guide teams on repository hygiene, modularization, access controls, and branching strategies.
• Troubleshoot ingestion, analysis, and runtime issues across code, infrastructure, and integrations.
• Provide architectural guidance and clearly communicate trade-offs when preparing systems for AI-driven workflows.
• Work directly with customer engineers to drive adoption and unblock progress.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Number of Employees: 5,001-10,000 employees