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.

How Jobgether works: We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team. We appreciate your interest and wish you the best!  Why Apply Through Jobgether?    Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.     #LI-CL1