Solution Architect

**About Providence**

Providence, one of the US’s largest not-for-profit healthcare systems, is committed to high quality, compassionate healthcare for all. Driven by the belief that health is a human right and the vision, ‘Health for a better world’, Providence and its 121,000 caregivers strive to provide everyone access to affordable quality care and services.

Providence has a network of 51 hospitals, 1,000+ care clinics, senior services, supportive housing, and other health and educational services in the US.

Providence India is bringing to fruition the transformational shift of the healthcare ecosystem to Health 2.0. The India center will have focused efforts around healthcare technology and innovation, and play a vital role in driving digital transformation of health systems for improved patient outcomes and experiences, caregiver efficiency, and running the business of Providence at scale.

**Why Us?**
- Best In-class Benefits
- Inclusive Leadership
- Reimagining Healthcare
- Competitive Pay
- Supportive Reporting Relation
- Job Title: Solution Architect- Experience Level: 8-12 Years- Job Summary:- Key Responsibilities:
- 1. Solution Design & Architecture:
- Lead the design and architecture of AI/ML solutions, especially those involving LLMs, ensuring they align with business objectives and technical feasibility.
- Develop end-to-end architectures for data pipelines, model training, deployment, and monitoring.
- Design scalable and optimized solutions leveraging cloud platforms (e.g., AWS, Azure, GCP) and containerized services (e.g., Docker, Kubernetes).
- 2. Large Language Model (LLM) Expertise:
- Fine-tune and deploy LLMs (e.g., GPT, BERT, T5, etc.) for business-specific use cases, ensuring model performance, accuracy, and efficiency.
- Optimize pre-trained LLMs for specific tasks, balancing computational cost and performance.
- 3. Technical Leadership & Innovation:
- Drive AI/ML innovation by staying up-to-date with the latest trends and breakthroughs in LLMs, AI, and ML, including emerging techniques in Transformer architectures and self-supervised learning.
- Guide data scientists and ML engineers in developing cutting-edge AI/ML solutions.
- Provide thought leadership and strategic insights into how LLMs can solve complex business problems and enhance existing solutions.
- 4. Collaboration & Stakeholder Management:
- Partner with product and business teams to understand requirements and translate them into AI/ML solutions that deliver measurable outcomes.
- Communicate complex technical concepts to non-technical stakeholders, providing clear explanations of AI/ML solutions and their business impact.
- 5. Model Development & Deployment:
- Lead the development of AI/ML models, including data preprocessing, feature engineering, model selection, and hyperparameter tuning.
- Deploy models in production environments, ensuring reliability, scalability, and performance monitoring.
- Implement MLOps best practices for continuous model monitoring, retraining, and lifecycle management.
- 6. Data & AI Governance:
- Ensure data privacy, security, and governance standards are adhered to in all AI/ML projects.
- Develop ethical AI practices, especially in the context of LLMs, ensuring transparency and fairness in AI models.
- Key Requirements:
- Educational Background:

- Bachelor’s or Master’s degree in Computer Science, Data Science, AI/ML, or related field.
- Ph.D. in AI/ML or related field is a plus.
- Technical Skills:

- Strong expertise in AI/ML technologies, including hands-on experience with LLMs (e.g., GPT, BERT, T5, etc.).
- Proficiency in Python, TensorFlow, PyTorch, Hugging Face, or other deep learning frameworks.
- Experience with cloud platforms (AWS, Azure, GCP) and containerization (Docker, Kubernetes).
- Knowledge of MLOps, CI/CD pipelines for model deployment, and version control for model artifacts.
- Experience:

- 8-12 years of experience in AI/ML roles with hands-on experience in designing AI architectures and deploying ML solutions in production.
- Experience in leading AI projects end-to-end from concept to deployment, particularly those involving LLMs.
- Proven track record of solving business problems using AI/ML in industries like healthcare, finance, e-commerce, or manufacturing.
- Soft Skills:

- Strong communication skills, with the ability to explain complex AI concepts to both technical and non-technical stakeholders.
- Leadership experience, including mentoring and guiding junior engineers.
- Problem-solving mindset with a strong ability to innovate and think strategically.
- Preferred Qualifications:
- Publications or patents related to AI/ML, especially in LLMs.
- Experience with other deep learning models like CNNs, RNNs, GANs, and Attention-based architectures.
- Familiarity with data privacy regulations (GDPR, HIPAA) and ethical AI practices.
- This role offers the opportunity to work on cutting-edge AI technologies, with a focus on deploying advanced LLMs to