AI Solutions Engineer Specialist Lead

Job Title : AI Solutions Engineer Specialist Lead

Location : Little Rock, Arkansas

Experience : 12+ Years

Employment Type : Contract

Interview Type : In-Person or Webcam

Job Description

The AI Solutions Engineer Specialist Lead will be responsible for leading the design, development, and deployment of advanced artificial intelligence and machine learning solutions that solve complex business problems. This role involves collaborating with cross-functional teams, driving strategic initiatives, and ensuring scalable and efficient AI solution delivery. The ideal candidate will have deep expertise in AI engineering, cloud platforms, modern data architectures, and leading innovation-driven projects.

Key Responsibilities

Lead the end-to-end lifecycle of AI solution development, including problem definition, data acquisition, model development, validation, deployment, and monitoring.

Architect and implement AI systems and MLOps pipelines for large-scale production environments.

Collaborate with product owners, business leaders, data scientists, and engineering teams to translate business requirements into technical solutions.

Lead research on emerging AI technologies and evaluate opportunities to integrate them into enterprise solutions.

Drive automation, optimization, and continuous improvement of AI models and workflows.

Provide technical leadership, mentorship, and guidance to engineering teams and junior AI developers.

Conduct performance tuning, model retraining, and scalability assessments.

Ensure compliance with security, privacy, ethical AI, and regulatory standards.

Lead proof-of-concept initiatives and present recommendations to senior stakeholders.

Document system architecture, implementation patterns, and operational processes.

Required Qualifications

12+ years of experience in software engineering or data / AI engineering, with at least 5+ years focused on AI and ML system development.

Strong expertise in machine learning algorithms, deep learning frameworks (TensorFlow, PyTorch, Keras), and classical ML tools (Scikit-learn).

Hands-on experience building production-grade AI and data pipelines using cloud platforms (AWS, Azure, or Google Cloud).

Proficiency in Python, SQL, and ML engineering tools such as MLflow, Kubeflow, Airflow, or similar pipelines.

Experience with large-scale data processing using Spark, Databricks, or equivalent technologies.

Strong understanding of MLOps best practices, CI / CD pipelines, containerization, Kubernetes, and model deployment strategies.

Proven ability to architect distributed systems and data-driven applications.

Experience with NLP, generative AI, computer vision, or LLM-based solutions.

Excellent communication skills and experience working with business stakeholders and technical teams.

Bachelor's or Master's degree in Computer Science, Engineering, Data Science, AI / ML, or related field.

Preferred Skills

Experience with vector databases, embeddings, RAG frameworks, and LLM integrations.

Hands-on experience with enterprise AI platforms such as Azure OpenAI, Amazon Bedrock, or Google Vertex AI.

Familiarity with model governance, ethical AI implementation, and responsible AI frameworks.

Knowledge of microservices architecture and API design.

Experience working in Agile development environments.

Certifications in cloud or AI engineering.