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AI Architect

Dallas, TX

Employment Type: Direct Hire Job Number: 27333 Pay Rate: $150000 - $180000 Remote Friendly?: Hybrid

Job Description


Job Title: AI Architect

Overview
A fast-growing technology team is looking for a hands-on AI Architect to lead the design, development, and deployment of scalable AI-powered solutions. This role demands deep technical expertise in artificial intelligence, machine learning, and cloud-native systems, with a focus on building real-world applications through rapid prototyping and iterative development. You’ll work closely with cross-functional teams to lead both internal and customer-facing projects, taking AI solutions from concept to production.

Key Responsibilities

  • Design scalable AI/ML architectures for enterprise applications using cloud-native tools and best practices.

  • Lead full ML lifecycle: data ingestion, feature engineering, model training, evaluation, deployment, and monitoring.

  • Apply advanced ML techniques such as deep learning, transformers, reinforcement learning, and generative models to solve business problems.

  • Provide technical mentorship to ML engineers and data scientists, including code reviews and model performance tuning.

  • Implement MLOps practices including CI/CD for ML, model versioning, reproducibility, and standardized pipelines.

  • Champion responsible AI standards —fairness, interpretability, privacy, and compliance.

  • Optimize AI workloads on major cloud platforms like AWS, Azure, or GCP.

Required Qualifications

  • Bachelor’s or Master’s in Computer Science, Data Science, or AI (PhD preferred).

  • 8+ years in AI/ML solution development with at least 3 years in an architectural or leadership role.

  • Strong coding skills in Python and experience with ML frameworks like TensorFlow, PyTorch, scikit-learn, Keras, and SageMaker.

  • Solid understanding of algorithms, data structures, probability, statistics, and optimization techniques.

  • Practical experience using cloud-based AI/ML tools such as SageMaker, Vertex AI, and Azure ML.

  • Track record of deploying ML models to production at scale.

  • Experience working with data lakehouse environments, distributed data processing frameworks like Spark and orchestration tools like Airflow.

  • Hands-on experience with MLOps: deployment, monitoring, and retraining pipelines.

  • Experience with OCR, Generative AI, and LLMs (e.G., ChatGPT, Claude, Gemini).

  • Familiarity with generative models like GPT, DALL·E, Stable Diffusion and prompt engineering.

  • Exposure to edge AI, large-scale NLP, and computer vision.

  • Experience with container technologies (Docker, Kubernetes) for AI deployment.

  • Proficiency with cloud services (AWS, Azure, GCP).

  • Strong communication and leadership skills —able to translate complex ML topics into actionable strategies.
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About Dallas, TX

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