AI Engineer

TrustNet Technologies; United States; Remote; USD 140,000 - 190,000; Full time

Job summary

TrustNet Technologies is seeking a hands-on AI/ML Engineer to design, build, and scale intelligent systems that drive automation and decision making across the organization. This role focuses on applied AI, large language models, automation, and production‑grade pipelines, with emphasis on real‑world deployment and measurable impact.

You will develop AI driven workflows, train and fine‑tune models, build APIs and data pipelines, and collaborate with cross‑functional teams to deliver scalable

Qualifications

• Strong foundation in AI/ML with production deployment experience.
• Experience with large language models and model evaluation.
• Familiarity with data preprocessing and model serving.
• Ability to translate business needs into AI solutions.

Responsibilities

• Design, develop, and deploy AI‑driven solutions for business operations.
• Train, fine‑tune, and optimize ML models and LLMs.
• Build AI‑enabled workflows and intelligent pipelines.
• Develop APIs and services connecting AI to applications.
• Ensure solutions are scalable, reliable, and production‑ready.
• Collaborate across teams to identify AI opportunities.
• Monitor performance and improve accuracy over time.
• Document architecture and best practices.
• Stay current with trends in AI, LLMs, and intelligent systems.
• Design and manage data/infrastructure powering AI systems.
• Build end-to-end applications delivering AI capabilities to users.
• Design and develop full‑stack apps and dashboards.

Skills

Python

Machine learning

TensorFlow

PyTorch

NLP

API development

Data pipelines

LLMs

Cloud platforms

Production systems

Tools

IBM watsonx

Red Hat Ansible

OpenShift

Job description

AI Engineer (Remote USA or LATAM)

TrustNet Technologies is seeking a highly capable and hands‑on AI / ML Engineer to design, build, and scale intelligent systems that drive automation, decision‑making, and business operations across the organization. This role is centered on applied AI, with a strong emphasis on large language models (LLMs), automation, and production‑grade systems. We are looking for individuals who can take AI from concept to real‑world deployment and deliver measurable impact. Candidates may come from a Data Engineering or Full‑Stack Engineering background, but must have a strong foundation in AI/ML and a passion for building intelligent, scalable solutions.

Responsibilities

• Design, develop, and deploy AI‑driven solutions for business operations and strategic initiatives
• Train, fine‑tune, and optimize machine learning models and LLMs for real‑world use cases
• Build and maintain AI‑enabled workflows, automation systems, and intelligent pipelines
• Develop and integrate APIs and services that connect AI models to business applications
• Ensure solutions are scalable, reliable, and production‑ready
• Collaborate with cross‑functional teams to identify opportunities for AI and automation
• Monitor and improve system performance, accuracy, and efficiency over time
• Document system architecture, workflows, and best practices
• Stay current with emerging trends in AI, LLMs, and intelligent systems
• We are looking for candidates who can design and manage the data and infrastructure layer that powers AI systems.
• Additional Responsibilities
• Design and maintain data pipelines for ML workflows
• Build and manage data ingestion, processing, and transformation systems
• Enable real‑time or batch data processing for AI applications
• Ensure data quality, availability, and scalability
• Support model training pipelines and feature engineering systems
• We are looking for candidates who can build end‑to‑end applications that deliver AI capabilities to users.
• Additional Responsibilities
• Design and develop full‑stack applications (front‑end + back‑end)
• Build user interfaces, dashboards, and internal tools
• Integrate AI models into customer‑facing or internal applications
• Develop APIs, services, and application logic
• Ensure excellent user experience and usability of AI systems

Qualifications

• Preferred Qualifications (Nice to Have)
• Experience with IBM watsonx
• Experience with Red Hat Ansible and OpenShift
• Knowledge of Microsoft ecosystem / Foundation Platform
• Familiarity with DevOps practices and CI/CD pipelines
• Experience working in fast‑paced, high‑impact environments

Required Skills

• Core Technical Requirements (All Candidates)
• Strong proficiency in Python
• Experience with machine learning algorithms and model development
• Experience with TensorFlow, PyTorch, or similar frameworks
• Knowledge of NLP and/or deep learning
• Experience with model deployment and production environments
• Experience building or integrating REST APIs
• Understanding of data preprocessing and transformation (e.g., Pandas)
• Familiarity with cloud ML platforms and scalable systems
• Strong foundation in statistical modeling and problem‑solving
• Core Soft Skills
• Strong communication skills (ability to explain technical concepts clearly)
• Excellent problem‑solving ability