Jd
- Recommend and develop AI systems and frameworks for applications and products.
- Present AI/ML concepts to leadership; lead prototype and MVP development to validate solutions.
- Design and implement cloud architecture for large-scale AI systems.
- Build and scaffold robust data pipelines for complex AI systems.
- Develop specifications and code for low-latency APIs/services to deploy AI models into applications.
- Monitor model and AI system performance to ensure reliability.
- Participate actively in agile-like team development practices.
- Create and maintain thorough, consistent documentation.
- Conduct and participate in peer reviews of code and deliverables.
- Guide and mentor AI engineers on best practices and methodologies.
- Stay updated on new AI/ML tools, technologies, and industry trends.
- Advise on enterprise AI technology, infrastructure, and strategy roadmaps.
- Collaborate with external stakeholders to conceptualize AI solutions aligned with business value and governance.
- Provide thought leadership within the Premera AI community.
- Perform additional duties as assigned.
### Minimum Qualifications
- Bachelor’s degree in Computer Science, Statistics, Mathematics, or related field; or 2+ years of related professional IT/analytics experience.
- At least 5 years of experience in developing, deploying, and maintaining AI/ML systems (advanced degrees or certifications may substitute up to 2 years of experience).
### Preferred Qualifications
- 6+ years developing deep learning models (TensorFlow, PyTorch, MLX, JAX, Theano, Caffe, etc.).
- Experience with design patterns, microservices, and container orchestration (3+ years in production environments).
- 3+ years implementing ethical AI practices (explainability, fairness, bias mitigation).
- 3+ years expertise in advanced prompt engineering techniques (Retrieval Augmented Generation, Tree of Thoughts, Multimodal CoT), leading teams and setting best practices.
- 4+ years experience productionizing AI models, building scalable pipelines, and robust monitoring systems.
- 5+ years working in Agile-like environments.
### Knowledge, Skills, and Abilities
- Strong background in deep learning architectures (CNNs, transformers, GANs, LSTMs, GNNs, Autoencoders, Diffusion Models, NODEs).
- Expertise in advanced prompt engineering techniques and team leadership.
- Experience debugging, optimizing, and tuning AI systems.
- Knowledge of software design patterns, distributed computing, microservices, and container orchestration.
- Proficient in Python and ML libraries (NumPy, Pandas, Matplotlib, scikit-learn).
- Experience with traditional ML lifecycles and minimal interface tools (Streamlit, Shiny).
- Proficient in ethical AI practices (explainable AI, fairness, bias mitigation).
- Strong communication, collaboration, and mentorship capabilities.
- Ability to explain technical AI/ML concepts to non-technical stakeholders clearly.
