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

Dallas, TX, US • Posted 3 hours ago • Updated 25 minutes ago

Contract Independent

Contract Corp To Corp

Contract W2

75% Travel Required

On-site

VDart, Inc.

Fitment

Dice Job Match Score™

👾 Reticulating splines...

Job Details

Skills

Python
Devops
Cloud

Summary

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

Location: Dallas, TX (Onsite)

Type: Contract

Description:

POSITION OVERVIEW: AI Solutions Engineer (Python, DevOps, Cloud, LLM)

As an AI Solutions Engineer, you are a hands-on engineer responsible for deploying, configuring, and operating the Client's AMS AI Platform in customer environments. You will work directly with customer engineering teams to install the platform, integrate it into existing DevOps workflows, ingest and analyze codebases, and ensure the solution delivers real, measurable value.

Key Responsibilities

Platform Installation & Engineering
Deploy and configure the 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.
Code & Workflow Enablement
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.
Technical Discovery & Solutioning
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.
Customer & Internal Collaboration
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.

Basic Qualifications:

Bachelor's degree in Computer Science, Information Technology, or a related field, or equivalent practical experience.
Minimum 2+ years of experience in a technical implementation or solutions engineering role, preferably with a SaaS product.
Minimum 2+ years of experience with Azure, OpenAI, and other cloud and LLM providers
Minimum 7+ years strong in software development lifecycle (SDLC) practices and common source control workflows (e.g. Git branching strategies, pull requests, release versioning).
Ability to provide architectural guidance and communicate trade-offs when preparing code for analysis workflows.
Minimum 5+ years of strong understanding of software integration principles and APIs.
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.
Ability to travel to client sites as needed

Key Skills

Programming proficiency in Python, R, and Java
Relevant AI libraries (TensorFlow, PyTorch).
Machine Learning and Deep Learning Expertise
Data Management and Processing.
Software engineering fundamentals including architecture, systems thinking, API integration, and CI/CD practices. Knowledge of cloud computing platforms (AWS, Azure, Google Cloud) for scaling and deployment. Understanding machine learning workflows and algorithms.

Degree: Bachelor's or Master's in Computer Science or related field.

Nice to Have; (But not a must)

SaaS products

Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.

Dice Id: 10330808
Position Id: 2026-94958
Posted 3 hours ago

Company Info

About VDart, Inc.

VDart, headquartered in Atlanta, GA, is a global leader in digital talent solutions and IT staffing, delivering top technology professionals to businesses worldwide. With a strong presence across North America, Europe and Asia, we specialize in helping organizations navigate complex technology landscapes with the right expertise.

Through a strategic, client-focused approach, we have placed over 20,000 professionals across key industries and advanced technology solutions. Whether placing top talent in cutting-edge roles or providing strategic digital workforce solutions, our network of 4,000 specialists across 13 countries is committed to excellence, agility and impact.

Backed by 18 years of industry experience, we go beyond staffing to build long-term partnerships that accelerate digital transformation and drive sustained growth. Whether you need a technology partner to fuel innovation or specialized workforce solutions to maintain a competitive edge, VDart delivers the right people, skills and mindset to create a lasting impact in a digital-first world.

Create job alert

Never miss an opportunity! Create an alert based on the job you applied for.