Bring your heart to CVS Health. Every one of us at CVS Health shares a single, clear purpose: Bringing our heart to every moment of your health. This purpose guides our commitment to deliver enhanced human-centric health care for a rapidly changing world. Anchored in our brand — with heart at its center — our purpose sends a personal message that how we deliver our services is just as important as what we deliver.
Our Heart At Work Behaviors™ support this purpose. We want everyone who works at CVS Health to feel empowered by the role they play in transforming our culture and accelerating our ability to innovate and deliver solutions to make health care more personal, convenient and affordable.

REQUIRED QUALIFICATIONS:

• 8+ years of experience as a Software Engineer, with a focus on Machine Learning.
• Proven experience in building and scaling RAG applications using frameworks like Langchain, LLamaIndex in production.
• 7+ years of Data & Analytics, specializing in the design and development of Data & ML pipelines and/or platforms.
• 6+ years of Hands-on experience with ML frameworks and libraries (e.g., TensorFlow, PyTorch, Scikit-learn etc.) and ML algorithms (i.e., clustering, decision trees, boosting, etc.)
• 5+ years of experience with data preprocessing, feature engineering and model evaluation
• 5+ years of experience developing production-level software with one or more languages, such as Python, Java, or C++.
• 5+ years of Experience with cloud platforms (e.g., AWS, Google Cloud, Azure) and containerization technologies (e.g., Docker, Kubernetes).
• Proficiency in defining API routes using HTTP methods like GET, POST, PUT, DELETE, and adept at handling request parameters and body data.
• Strong understanding of data structures, algorithms, and software design principles.

PREFERRED QUALIFICATIONS:

• Exposure in implementing Gen AI and/or NLP based solutions using LLMs.
• Develop Agentic AI applications and automate the orchestration workflows using Vertex AI Agent Builder, Langgraph, etc
• Familiarity with working in Dev/ML Ops model and CI/CD tools and infrastructure as a code (e.g., Jenkins, Docker, Kubernetes).
• Knowledge of implementing security mechanisms like OAuth2, JWT tokens, and basic authentication to safeguard API endpoints.
• Advanced SQL skills for complex query writing, optimization, and database management.
• Experience within an IT infrastructure domain and familiarity with telemetry/log data and concepts is highly desirable.
• Experience implementing or maintaining Feature Stores.
• Excellent problem-solving skills and a collaborative spirit that thrives in a team environment.
• Strong communication skills, with the ability to explain complex technical concepts to non-technical stakeholders in an engaging manner.

EDUCATION:

• Bachelor’s Degree or equivalent work experience in Computer Science, Data Science, Machine Learning, Data Engineering or related field required. Master’s Degree preferred.

• Innovate and Create: Design, develop, and maintain scalable software applications with complex Data/ ML solutions that push the envelope of technology.
• Performance Guru: Monitor and evaluate the performance of ML models in production, making necessary adjustments to meet high standards for performance and reliability.
• API Wizardry: Build and deploy RESTful APIs using Fast API to serve ML models and facilitate smooth data interactions, ensuring a seamless user experience.
• Collaborative Synergy: Partner with data scientists to understand model requirements and translate them into production-ready code that delivers results.
• Algorithm Alchemist: Implement and optimize algorithms for data processing, feature extraction, and model training, turning raw data into actionable insights.
• Quality Advocate: Conduct code reviews and provide constructive feedback, ensuring high-quality code and adherence to best practices that elevate our standards.
• Lifecycle Champion: Participate in the full software development lifecycle, from requirements gathering to design, implementation, testing, and deployment, ensuring a smooth process every step of the way.
• Continuous Learner: Stay ahead of the curve by keeping up to date with the latest advancements in ML and software engineering, applying new techniques and technologies to our projects.
• Knowledge Sharer: Document processes, code, and model performance to ensure knowledge sharing and maintainability, fostering a culture of learning within the team.