AI Engineer

Accountabilities

• Design, develop, test, and deploy AI and machine learning applications that solve business and customer problems.
• Build generative AI solutions using large language models, retrieval-augmented generation (RAG), AI agents, embeddings, and prompt engineering.
• Integrate AI capabilities into existing products, platforms, and business workflows.
• Develop data pipelines and supporting services for model training, evaluation, and inference.
• Establish evaluation frameworks to assess model accuracy, reliability, safety, latency, and cost.
• Monitor AI applications in production and continuously improve their performance, scalability, and reliability.
• Implement responsible AI practices covering privacy, security, bias mitigation, and appropriate human oversight.
• Document system architecture, technical decisions, experiments, processes, and operational procedures.
• Collaborate with software engineers, product managers, data scientists, and subject-matter experts throughout the development lifecycle.
• Stay current with developments in AI research, platforms, tools, frameworks, and engineering best practices.

Requirements

• Bachelor's degree in Computer Science, Engineering, Data Science, Information Technology, or a related technical discipline preferred; equivalent education and experience may be considered.
• 5+ years of experience in software engineering, machine learning engineering, or a related technical field.
• 3+ years of professional experience with Python and software development best practices.
• 3+ years of hands-on experience with generative AI and large language models.
• Experience with AWS Bedrock, Amazon SageMaker, Docker, JupyterLab, and AI-powered Optical Character Recognition (OCR).
• Familiarity with APIs, cloud platforms, databases, version control, software testing, and CI/CD practices.
• Strong understanding of machine learning concepts, data preparation, and model evaluation.
• Experience with frameworks such as PyTorch, TensorFlow, LangChain, or comparable technologies is desirable.
• Experience with vector databases, retrieval systems, MLOps, model monitoring, and scalable inference is a plus.
• Familiarity with Salesforce and MuleSoft is advantageous.
• Knowledge of responsible AI, data privacy, and AI security practices is beneficial.
• Demonstrated ability to take AI solutions from prototype through production.
• Strong analytical, problem-solving, communication, and cross-functional collaboration skills.
• Ability to obtain a medium-level Government Public Trust security background check.

Benefits

• Competitive annual salary of $130,000–$135,000 USD.
• Comprehensive benefits designed to support health, well-being, and financial security.
• Medical, dental, and vision coverage may be available.
• Paid time off and company holidays.
• Opportunities for professional growth, learning, and development.
• Opportunity to work on innovative AI and machine learning solutions in a collaborative environment.
• Remote work arrangement.