Worldpac
Linkedin · Posted 2mo ago
Senior AI Engineer
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Indexed description
We are seeking a technically skilled Senior AI Engineer to design, develop, and deploy AI-powered solutions across our organization. Your work will include building AI chat assistants, integrating AI with databases and business systems, and automating processes to drive efficiency and innovation.
Key Responsibilities
- Translate product requirements and user stories into robust AI/ML solutions
- In collaboration with external partners, design, develop, and deploy AI-powered chat assistants and automation tools for internal teams
- Integrate AI solutions with existing databases, APIs, and business applications
- Build, train, evaluate, and maintain machine learning models, with a focus on production readiness and scalability
- Collaborate with IT and data teams to ensure data quality, security, and compliance
- Document technical designs, code, and deployment processes
- Stay current with advancements in AI/ML technologies and recommend best-fit solutions
- Provide technical support for deployed AI systems and assist with troubleshooting as needed
- Bachelor’s degree in computer science, Engineering, Data Science, or a related field; or equivalent combination of education and relevant professional experience
- 6 - 8 years of hands-on experience developing and deploying AI/ML solutions in a production environment, with at least 4 years specifically focused on LLM-based GenAI applications
- Proven experience developing LLM agents using frameworks such as LangChain, AutoGen, or similar orchestration layers
- Proficiency in Python and relevant AI/ML frameworks (e.g., TensorFlow, PyTorch, scikit-learn)
- Experience with natural language processing (NLP) and building chatbots or conversational AI systems
- Strong knowledge of database systems and data integration
- Experience with cloud platforms (AWS, Azure, GCP) for deploying AI solutions
- Ability to write clean, maintainable, and well-documented code
- Strong problem-solving skills and attention to detail
- Experience with MLOps practices and tools for model deployment and monitoring
- Experience working in agile, cross-functional teams
- Experience with RPA (Robotic Process Automation) tools
- Knowledge of data privacy and security best practice
- Work closely with the Product Manager, who will define and prioritize AI projects and features
- Collaborate with IT, data, and business teams to ensure seamless integration and deployment of AI solutions
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