AI Platform Engineer

Key Details

• Compensation: $170,000 – $180,000 with potential Bonus 

• Location: Arlington, TX

• Work Model: ONSITE 4 to 5 Days a week 

• Benefits: Are eligible to enroll in benefits, including medical, dental, and vision

• Employment Type: Full Time

• Work Authorization: Applicants must be currently authorized to work in the United States on a full-time basis; our client will not sponsor applicants for work visas now or in the future

AI Platform Engineer
We are seeking an experienced AI Platform Engineer to help build and support scalable infrastructure for machine learning and generative AI solutions. This individual will focus on creating reusable platform capabilities that allow technical teams to move AI solutions into secure, reliable production environments.

• Build and maintain platforms supporting machine learning and generative AI workloads

• Develop reusable services for model deployment, APIs, data retrieval, search, automation, and monitoring

• Create automated deployment processes using CI/CD and infrastructure-as-code

• Support cloud, hybrid, and containerized infrastructure

• Improve platform reliability, security, performance, scalability, and cost efficiency

• Partner with engineering, architecture, security, data, and business teams

• Evaluate emerging AI technologies and help determine their practical business applications

• Contribute to proof-of-concept initiatives and new platform capabilities

Required Qualifications

• Bachelor’s degree in Computer Science, Engineering, Information Systems, or a related field, or equivalent professional experience

• 5+ years of experience in MLOps, ML engineering, platform engineering, cloud engineering, DevOps, or a related area

• Strong Python skills

• Hands-on experience with containers, orchestration platforms, APIs, CI/CD, infrastructure-as-code, and observability

• Experience deploying and supporting machine learning or generative AI workloads in production

• Familiarity with model serving, retrieval-augmented generation, vector search, AI agents, evaluation, monitoring, and platform security

• Ability to work independently, take ownership, and communicate effectively across technical and business teams

Preferred Qualifications

• Experience with enterprise cloud and AI platforms

• Experience supporting GPU-enabled or high-performance computing environments

• Familiarity with Kubernetes, ML lifecycle tools, AI gateways, model-routing solutions, or comparable technologies

• Experience working within a large or complex enterprise environment

• Experience helping build new products, platforms, or technical capabilities from the ground up

Ready to take the next step in your career? Apply today. We’re actively interviewing and excited to meet you.