Job title: AI/ML Engineer
Job type: Permanent
Emp type: Full-time
Industry: Technology
Functional Expertise: Machine Learning
Location: San Antonio, TX
Job published: 03/27/2026
Job ID: 152325

Job Description

AI/ML Solutions Engineer

Job Summary

Seeking a talented and driven AI/ML Solutions Engineer to join a team and play a pivotal role in designing and deploying intelligent systems that enhance operational efficiency and automate workflows. This is a hands-on, high-impact position that involves collaboration across finance, operations, and leadership teams. The ideal candidate will have expertise in building machine learning pipelines and developing scalable AI-driven solutions, with a particular focus on Generative AI and LLM-based applications.

Compensation Package

  • Competitive salary commensurate with experience
  • Comprehensive health, dental, and vision insurance
  • Generous paid time off and holidays
  • Professional development opportunities
  • Flexible work arrangements

Responsibilities

AI / Generative AI Development

  • Design and deploy AI/ML solutions using Google Cloud tools such as Vertex AI and APIs.
  • Identify and implement high-value use cases, including document processing, summarization, Q&A systems, and workflow automation.
  • Develop and optimize prompt engineering, RAG pipelines, and model tuning strategies.
  • Ensure AI solutions meet standards for accuracy, explainability, and compliance.
  • Apply safeguards such as data redaction, access controls, and secure prompt handling.

ML Engineering & Infrastructure

  • Build and maintain end-to-end ML pipelines, including data ingestion, deployment, and monitoring.
  • Leverage tools such as BigQuery, Dataflow, and orchestration frameworks.
  • Establish and implement MLOps best practices, including CI/CD, model versioning, and monitoring.
  • Design and maintain security-focused architecture, including encryption, IAM/least-privilege access, secure APIs, and logging/auditability.

Collaboration & Stakeholder Engagement

  • Partner with business teams to identify automation opportunities and translate business requirements into scalable AI/ML solutions.
  • Communicate technical concepts effectively to non-technical stakeholders.
  • Drive adoption of AI capabilities across the organization.

Qualifications/Requirements

Required Qualifications

  • Bachelor’s degree in a related technical field.
  • 3–5 years of experience in AI/ML, data science, or engineering roles.
  • Hands-on experience with Google Cloud tools such as Vertex AI and BigQuery.
  • Proficiency in working with LLMs, prompt engineering, and RAG frameworks.
  • Strong programming skills in Python and familiarity with ML frameworks like TensorFlow, PyTorch, or scikit-learn.
  • Knowledge of secure development practices and cloud security fundamentals.

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