Job Summary:

The AI Developer plays a key role in designing, developing, and deploying intelligent solutions. This role is focused on solving complex business challenges through innovative AI technologies and will collaborate closely with cross-functional teams to ensure timely and high-quality delivery of solutions aligned with defined objectives.

DS/Gen/Agentic AI resources with good hands-on skills on:

• Current Advancements: Generative AI, Agentic AI, LLM fine-tuning, RAG, GraphRAG, Vector databases, Knowledge Graph, Langchain, Langgraph, etc
• Model Deployment: MLOPs pipeline, CI/CD, Model Deployment, Docker, Kubernetes, Azure Cloud, Github, etc
• Core Skills: Traditional AI / ML / Data Science skillsets (Predictive, Prescriptive, Descriptive, Statistical, Optimization, Simulation, Natural Language processing, Computer Vision, Image Processing, etc)
• Domain: Healthcare, Facets, GuidingCare, etc

Note: Domain skills are nice to have and not mandatory.

Essential Functions:

• Design and implement AI models and algorithms tailored to diverse business challenges
• Define and lead the architecture of Generative AI platforms, including large language models (LLMs), vector databases, and inference pipelines
• Maintain deep expertise in modern generative AI technologies such as Knowledge Graphs, OpenAI, LLaMA, Python, LangChain, vectorization, embeddings, semantic search, Retrieval-Augmented Generation (RAG), Infrastructure as Code (IaC), and Streamlit
• Rapidly prototype proof-of-concept solutions to assess emerging technologies and innovative ideas
• Foster innovation and collaboration in a fast-paced environment through a hands-on, imaginative approach and a self-driven, inquisitive mindset
• Leverage AI-assisted development tools, including GitHub Copilot and internally developed solutions, to enhance productivity
• Apply creative problem-solving techniques to identify and implement process improvements
• Assess technical risks and develop effective mitigation strategies to ensure successful project delivery
• Collaborate with data scientists, software engineers, and product teams to integrate AI capabilities into production-ready systems
• Partner with leadership to evaluate existing services and develop strategies to optimize delivery and support
• Perform data preprocessing and analysis on large datasets to uncover actionable insights
• Train, validate, and fine-tune machine learning and deep learning models for optimal performance
• Deploy models using cloud infrastructure and containerization technologies such as Docker and Kubernetes
• Implement and manage MLOps pipelines to automate model training, deployment, monitoring, and lifecycle management
• Apply AIOps practices to enhance operational efficiency, automate incident detection, and optimize system performance using AI-driven insights
• Continuously monitor model performance and retrain as needed to maintain accuracy and relevance
• Stay current with industry trends, tools, and frameworks, and assess their applicability to organizational goals
• Document workflows, models, and codebases to support maintainability and knowledge sharing
• Provide timely and transparent progress updates to stakeholders, highlighting key milestones, challenges, and proposed solutions
• Perform any other job duties as requested

Education and Experience:

• Bachelor’s degree in Computer Science, Data Science, Artificial Intelligence or related field, or equivalent years of relevant work experience is required
• Master’s degree is preferred
• Minimum of five (5) years of experience in developing and deploying AI/ML models is required
• Experience with cloud platforms (AWS, Azure, GCP) and MLOps tools Is required
• Experience with Agile methodologies is required

Competencies, Knowledge, and Skills:

• Knowledge of model interpretability and ethical AI practices
• Proficiency in Python and libraries such as TensorFlow, PyTorch, Scikit-learn, and OpenCV
• Strong analytical, evaluative and problem-solving abilities
• Strong understanding of data structures, algorithms, and software engineering principles
• Excellent problem-solving skills and attention to detail
• Strong communication and collaboration abilities
• Knowledge of healthcare and managed care

Preferred Licensure and Certification:

• AI / Data Science certifications or credentials are preferred

Working Conditions:

• General office environment; may be required to sit or stand for extended periods of time
• Occasional travel may be required to meet with stakeholders and development teams

Compensation Range:

CareSource takes into consideration a combination of a candidate’s education, training, and experience as well as the position’s scope and complexity, the discretion and latitude required for the role, and other external and internal data when establishing a salary level. In addition to base compensation, you may qualify for a bonus tied to company and individual performance. We are highly invested in every employee’s total well-being and offer a substantial and comprehensive total rewards package.

Compensation Type (hourly/salary):

Organization Level Competencies

• Fostering a Collaborative Workplace Culture

• Cultivate Partnerships

• Develop Self and Others

• Drive Execution

• Influence Others

• Pursue Personal Excellence

• Understand the Business

This job description is not all inclusive. CareSource reserves the right to amend this job description at any time. CareSource is an Equal Opportunity Employer. We are dedicated to fostering an environment of belonging that welcomes and supports individuals of all backgrounds.