AI Engineer
Permanent/Full-Time Position
Atlanta, GA
Hybrid Work Schedule
Are you looking to take your career to the next level and support cutting-edge technology and AI initiatives in the healthcare space? We’re seeking a skilled and forward-thinking AI Engineer to join a newly established AI and emerging solutions team for with one of the largest healthcare providers in Georgia.
This is an exciting new role designed to help shape how artificial intelligence is leveraged to improve patient care, clinical decision-making, and operational efficiency—while upholding the highest standards of governance, regulatory compliance, and safety. As one of the founding members of the AI team, you will play a central role in building AI capabilities from the ground up, helping to implement trustworthy AI systems that are explainable, ethical, and aligned with the mission of delivering world-class healthcare. You will work cross-functionally with data scientists, clinicians, IT, and AI governance stakeholders to design, develop, deploy, and maintain machine learning solutions embedded into real-world healthcare environments.
Responsbilities Include:
- Partner with AI Product Analysts, Data Scientists, Software Engineers, and Clinical Teams to build and operationalize AI solutions that align with the organization’s clinical and business priorities.
- Collaborate with DevOps and Cloud teams to deploy scalable, reliable, and secure AI models into production environments.
- Design and manage MLOps pipelines supporting the full AI lifecycle—from data ingestion and model training to deployment, monitoring, and retraining.
- Work with Data Engineers to ensure efficient preprocessing, feature engineering, and integration with data pipelines.
- Serve as a technical lead or reviewer for third-party AI model integrations, helping assess risks and ensure compliance with healthcare regulations.
- Communicate AI system capabilities, limitations, and responsible use practices to clinical and operational stakeholders.
- Contribute to the establishment of internal AI development standards, governance frameworks, and monitoring practices to ensure patient safety and regulatory compliance.
- Stay current with emerging trends in AI governance, healthcare AI regulation (e.g., HIPAA, FDA AI/ML guidance, NIST frameworks), and fairness auditing.
- Complies with all policies, standards of work, and code of conduct
Required Minimum Experience:
- 5+ years in software engineering, process automation, or architecture
- 3+ years developing and deploying machine learning or AI-driven applications
- Strong hands-on experience with Python and/or Java, and AI/ML frameworks (e.g., TensorFlow, PyTorch, Scikit-learn, Keras, XGBoost)
- Proven success deploying AI models into production environments (cloud, edge, or on-premise)
- Expertise with MLOps practices including CI/CD for ML, versioning, monitoring, and automation
- Experience with cloud AI platforms (AWS SageMaker, Azure ML, Google Vertex AI), Docker, Kubernetes
- Familiarity with data engineering principles (ETL, preprocessing, feature pipelines)
- Strong understanding of AI model APIs, microservices, and model serving (e.g., FastAPI, Flask, TensorFlow Serving)
Preferred Experience and Skills:
- Background in healthcare data (EHRs, claims, HL7/FHIR standards)
- Knowledge of explainability tools (SHAP, LIME), bias/fairness auditing (Fairlearn, Aequitas)
- Understanding of AI privacy and compliance (HIPAA, ISO/IEC 42001, FDA AI/ML guidance, NIST Risk Framework)
- Experience with federated learning, edge AI, and privacy-preserving techniques
- Familiarity with NLP (BERT, GPT), computer vision (for medical imaging), or Graph Neural Networks
- Database experience with SQL, NoSQL, BigQuery, or Snowflake
Preferred Educational Background:
- Bachelor’s Degree in Artificial Intelligence, Computer Science, or related field
- Master’s or Doctorate in Artificial Intelligence or Machine Learning