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

Dallas, IA - USA

Monthly Salary: Not Disclosed

Posted on: Yesterday

Vacancies: 1 Vacancy

Job 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 Clients 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:

Bachelors 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: Bachelors or Masters in Computer Science or related field.

Nice to Have; (But not a must)

SaaS products

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 Clients A...