About the Role:
We are looking for a Lead AI Manager to work closely with the AI Product Lead in designing, developing, and deploying AI-driven solutions. This role bridges AI solution architecture and data engineering, focusing on Natural Language Processing (NLP), Computer Vision, scalable software architectures, and robust data pipelines. The ideal candidate will have expertise in AI/ML development, data processing, and software engineering, ensuring seamless data integration for AI-driven insights. This role involves collaborating with cross-functional teams to build high-impact AI applications.
Key Responsibilities:
- Collaborate with the AI Product Lead to define and drive the technical roadmap for AI and data-driven products.
- Architect and develop AI solutions for both in-house applications and consulting engagements.
- Design and implement data pipelines and ETL workflows to process unstructured data (PDFs, Word, Excel) into structured formats for analysis and AI models.
- Create and maintain APIs to integrate structured data with AI, visualization, and reporting systems.
- Optimize system architecture to ensure scalability, reliability, and security of AI-driven applications.
- Ensure best practices in software development, including CI/CD, testing, and code quality.
- Collaborate with data scientists, cloud engineers, and software developers to align data engineering outputs with AI/ML requirements.
- Develop and manage data storage solutions for real-time and retrospective analysis.
- Establish mechanisms for validating, monitoring, and ensuring data accuracy within AI-driven pipelines.
- Stay up to date with advancements in AI, ML, and data engineering trends.
Requirements:
- Bachelor's or Master's degree in Computer Science, Software Engineering, Data Engineering, or a related field.
- 8+years of experience in AI/ML, software development, and/or data engineering, with at least 3 years in an architecture-focused role.
- Hands-on experience with AI/ML frameworks (TensorFlow, PyTorch, Hugging Face) and data pipeline frameworks (Apache Airflow).
- Proficiency in Python, SQL, and data processing libraries (Pandas, OpenPyXL, PyPDF).
- Experience with cloud platforms (AWS, Azure, GCP) and deploying AI models in production.
- Strong understanding of database design, including relational and non-relational databases.
- Experience integrating unstructured document data into structured databases for AI applications.
- Deep understanding of software architecture, microservices, and DevOps practices.
- Strong problem-solving skills and ability to work in a fast-paced, dynamic environment.
- Excellent communication and collaboration skills.
Nice to Have:
- Experience with MLOps and AI model lifecycle management.
- Knowledge of regulatory and ethical considerations in AI development.
- Experience with construction or real estate performance metrics (if applicable).
- Contributions to open-source AI/ML or data engineering projects.
