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# Artificial Intelligence Engineer

- **Company:** Gridiron IT Solutions LLC
- **Location:** Chantilly, VA, United States
- **Experience:** Expert
- **Salary:** $150,000.0 - $190,000.0
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Computer Vision, Microsoft Azure, Cloud Computing, Computer Programming, Continuous Integration, Data Structures, Distributed Computing Environment, Distributed Systems, Python (Programming Language), Machine Learning, Tensorflow, Azure Machine Learning, Secure Coding, Reinforcement Learning, Pytorch, Large Language Models, Generative AI, Agentic-AI, Containerization, Scikit Learn, Low Latency, Machine Learning Operations, Api Design, Data Pipelines, Microservices
- **Published:** October 29, 2026
- **Apply:** https://www.careerboard.com/us/en/find-jobs-in-United-States/-865FE9E2258EA2177A/

## About the Role

Designs, develops, and deploys scalable, production-ready AI, machine learning (ML), and generative AI systems by building data pipelines for model training, evaluation, and inference, implementing algorithms in languages like Python, and operationalizing models using MLOps, CI/CD, containerization, and monitoring frameworks. This role designs and maintains APIs and microservices, optimizes models for accuracy, latency, and scalability, and ensures compliance with established AI governance, documentation, and ethical standards. Personnel must possess advanced Python programming skills and practical experience with ML frameworks, a solid understanding of data structures, algorithms, and distributed systems, and hands-on familiarity with cloud platforms. Requirements include proven experience deploying production-level GenAI models, vector databases, embeddings, or LLM-based applications, alongside technical competence in agentic AI, tool-calling, or multi-step reasoning, working knowledge
of MLOps platforms, a background in NLP, computer vision, or reinforcement learning, and experience operating within agile engineering teams.

Advanced Python skills and strong understanding of algorithms, data structures, and distributed systems.

Hands-on experience deploying production GenAI/LLM systems, embeddings, and vector databases.

Proficiency with PyTorch, TensorFlow, scikit learn, and cloud platforms (AWS, Azure, or GCP).

Practical experience with MLOps tools such as MLflow, Azure ML, or Vertex AI.

Background in NLP, computer vision, or reinforcement learning.

Preferred Qualifications

Experience in federal, defense, or highly regulated environments.

Knowledge of ethical AI, governance frameworks, and secure development practices.

Skills in large-scale optimization, GPU acceleration, or distributed training.

Experience building APIs, microservices, and automated ML workflows.