AI Solutions Lead Engineer

Job Title : AI Solutions Lead Engineer

Location : Sacramento, California

Experience Required : 12+ Years

Employment Type : Contract

Interview Type : In-Person or Webcam

Job Overview

We are looking for an experienced AI Solutions Lead Engineer who can guide the design, development, and deployment of advanced AI and machine learning solutions. This role requires someone who understands both the technical depth of AI systems and the business value they enable. You will work closely with cross-functional teams, lead solution architecture, ensure scalability, and provide technical leadership throughout the project lifecycle.

Key Responsibilities

Lead end-to-end AI solution development, from problem definition and data strategy to architecture design and production deployment.

Work with stakeholders to understand business needs and translate them into AI-driven solutions.

Design and implement machine learning pipelines, including model training, validation, testing, and optimization.

Collaborate with data engineers, data scientists, and software teams to ensure smooth integration of AI components into existing systems.

Oversee the development of prototypes, proof-of-concepts, and production-ready ML models.

Evaluate AI and ML frameworks, libraries, cloud services, and tools to recommend the best technical stack.

Ensure all solutions meet performance, scalability, and security standards.

Provide mentorship and technical leadership to junior engineers and data scientists.

Support model monitoring, debugging, and continuous improvement after deployment.

Prepare technical documentation, architecture diagrams, and project reports.

Required Skills & Experience

12+ years of experience in software engineering, AI / ML development, or related technical fields.

Strong hands-on experience with machine learning frameworks such as TensorFlow, PyTorch, Scikit-learn, or similar.

Proficiency in Python and experience with AI-related libraries, APIs, and toolkits.

Experience designing scalable AI / ML solutions in cloud environments (AWS, Azure, or Google Cloud).

Solid understanding of data engineering concepts, including data pipelines, ETL processes, and distributed systems.

Strong knowledge of MLOps practices, CI / CD pipelines, and model deployment strategies.

Ability to lead technical discussions, drive architecture decisions, and present solutions to technical and non-technical stakeholders.

Understanding of responsible AI principles, data privacy, and compliance requirements.

Excellent problem-solving, analytical thinking, and communication skills.

Preferred Qualifications

Prior experience building large-scale AI systems or enterprise AI platforms.

Experience working in an Agile or hybrid environment.

Familiarity with LLMs, vector databases, prompt engineering, or generative AI technologies.

Knowledge of Kubernetes, Docker, API development, or microservices architecture.