AI Developer

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