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

NTT DATA North America is a leading business and technology services provider, committed to accelerating client success through innovation. They are seeking an AI Solutions Engineer to deploy and operate the NTT Data AMS AI Platform in customer environments, working closely with engineering teams to ensure effective integration and functionality. Responsibilities: Deploy and configure the NTT Data AMS AI Platform within customer cloud environments; 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; Review customer codebases (language-agnostic) to assess structure, dependencies, and readiness for AI-driven analysis; Guide teams on repository hygiene, modularization, access controls, and branching strategies; Integrate the platform into customer CI/CD pipelines and release governance models; Troubleshoot ingestion, analysis, and runtime issues across code, infrastructure, and integrations; Lead technical discovery sessions to understand customer architecture, development workflows, and constraints; Translate business and engineering goals into practical platform configurations and deployment patterns; Provide architectural guidance and clearly communicate trade-offs when preparing systems for AI-driven workflows; Identify risks early (security, scale, complexity) and adjust implementation approach accordingly; Work directly with customer engineers to drive adoption and unblock progress; Partner with Product, Support, and Engineering to surface platform gaps, edge cases, and improvement opportunities; Document configurations, patterns, and lessons learned to improve future deployments; Serve as the technical point of continuity across installation, enablement, and early production usage Qualifications: 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 Required Skills: Python, Java, Machine Learning, Deep Learning, Azure, OpenAI, DevOps, Kubernetes, Git, Software Integration, APIs, Problem solving, Communication