Senior AI Engineer

Job Description

The Senior AI Engineer, based in Lewisville, TX, will design and architect scalable AI and machine learning solutions that align with enterprise goals while leading the development, training, fine‑tuning, and optimization of advanced ML models and large language models for real‑world applications.

Location: Lewisville, TX

Position Type: Full-Time

Hours: 9:00 am to 5:00 pm Weekdays (Monday – Friday)

Key Responsibilities

Design and architect scalable artificial intelligence and machine learning solutions aligned with enterprise business objectives and technical requirements.
Develop, train, fine-tune, evaluate, and optimize machine learning models and large language models (LLMs) for real-world applications.
Implement advanced generative AI solutions including conversational AI, document processing, summarization, and intelligent automation systems.
Design and build Retrieval-Augmented Generation (RAG) pipelines to enhance knowledge-based AI systems using structured and unstructured enterprise data.
Create AI agents and workflow automation solutions to streamline operational processes and improve efficiency.
Develop end-to-end AI pipelines covering data ingestion, data preprocessing, feature engineering, model training, evaluation, deployment, and continuous improvement.
Integrate AI models into enterprise applications using REST APIs, microservices architecture, and event-driven systems.
Deploy and maintain AI solutions on cloud platforms such as Microsoft Azure, AWS, or GCP using scalable and resilient architectures.
Work with vector databases, embeddings, and semantic search technologies to support intelligent retrieval and context-aware AI systems.
Implement MLOps best practices including version control, automated testing, continuous integration and deployment, monitoring, and model lifecycle management.
Optimize model performance, scalability, and resource utilization to ensure efficient production deployments.
Collaborate with data engineers, software developers, product managers, and business stakeholders to translate requirements into technical AI solutions.
Perform research and evaluation of emerging AI technologies and frameworks to improve system capabilities and innovation.
Develop reusable AI components, frameworks, and best practices to support enterprise-wide AI adoption.
Ensure compliance with data governance, security standards, privacy regulations, and ethical AI principles.
Provide technical leadership, mentorship, and guidance to engineering teams, including code reviews and architecture reviews.
Troubleshoot complex AI system issues and implement solutions to improve performance and reliability.
Document AI architectures, workflows, and technical designs to support knowledge sharing and maintainability.

Participate in strategic planning and contribute to defining AI roadmaps aligned with organizational goals.

Technical Experience

Minimum Degree Requirement: Bachelor’s degree in Computer Science, Information Technology, Software Engineering, or a closely related field.

Minimum work Experience:

3 years total professional experience in artificial intelligence, machine learning, or software engineering.

Minimum years of experience must include the following:

3 years of experience in programming skills in languages such as Python, C#, Java, or similar.
Hands-on experience with machine learning and deep learning frameworks (e.g., TensorFlow, PyTorch, Hugging Face, or equivalent).
Experience developing and deploying AI solutions including natural language processing (NLP), predictive analytics, or generative AI applications.
Knowledge of Large Language Models (LLMs), prompt engineering, or AI automation workflows.
Experience integrating AI models into production systems using APIs or microservices architecture.
Familiarity with cloud platforms such as Microsoft Azure, AWS, or Google Cloud Platform.
Understanding of data preprocessing, feature engineering, and working with structured and unstructured datasets.
Knowledge of software development lifecycle practices, version control, and CI/CD concepts.
Strong analytical, problem-solving, and technical documentation skills.
Ability to collaborate effectively with cross-functional teams in an enterprise environment.