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