Senior AI Engineer

This is a fully remote position, open to applicants in Texas.

📋 Description

• Design, develop, and train machine learning, deep learning, time series, Generative AI, predictive analytics, Natural Language Processing, and Image Processing solutions tailored for healthcare applications.

• Create, test, and implement AI solutions across both cloud-based and on-premises environments.

• Handle large healthcare datasets, executing data preprocessing, feature engineering, and model training while maintaining compliance with HIPAA and other regulations.

• Build APIs and integrations.

• Optimize and implement AI models within Gainwell’s existing technology framework.

• Collaborate with software engineers to facilitate smooth integration.

• Employ ML Ops and LLM Ops practices, assess model performance, and consistently monitor ML/DL and LLM outcomes.

• Enforce security protocols in Generative AI solutions and establish guard rails.

• Oversee, refine, and enhance AI/Generative AI models for accuracy, efficiency, and speed.

• Stay informed on advancements in AI/ML/Generative AI and investigate new technologies and methodologies.

• Guarantee that AI implementations comply with healthcare regulations, ethical AI standards, and data privacy guidelines.

• Discover opportunities to automate workflows and enhance business processes through AI-driven solutions.

⛳️ Requirements

• A minimum of 3 years of experience in AI/ML engineering, encompassing the development, deployment, and optimization of enterprise AI solutions, machine learning models, and large language model (LLM) applications.

• Expertise in Generative AI technologies, including LLM fine-tuning, Retrieval-Augmented Generation (RAG), Agentic AI frameworks, LangChain, LangGraph, CrewAI, OpenAI Swarm, vector databases, and graph databases.

• Strong software development and data engineering capabilities.

• Proficiency in Python, TensorFlow, PyTorch, SQL, big data technologies (Spark, Hadoop), and contemporary AI frameworks.

• Experience in deploying scalable AI solutions within cloud environments such as AWS, Azure, or GCP.

• Familiarity with MLOps, model optimization, inference efficiency, and production-quality AI architecture.

• Proven technical leadership and solution architecture experience.

• Capacity to translate business needs into AI-driven solutions.

• Ability to lead cross-functional teams and engage with stakeholders effectively.

• Experience in developing user-facing applications using Streamlit (required) and modern front-end technologies.

• Video cameras must be utilized during all interviews and throughout the initial week of orientation.

🏝️ Benefits

• Flexible working arrangements.

• Opportunities for learning and career advancement.

• Access to technical credentials and certifications.

• Generous and flexible vacation policy.

• Educational assistance programs.

• Leadership and technical development academies.

• Occasional travel opportunities (0-10%).

• 401(k) employer matching.

• Comprehensive health benefits.