Senior AI Automation Engineer

Posted 1mo ago

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Architect and deliver production-grade AI and machine learning systems
Lead design and deployment of predictive and generative AI models
Own architectural decisions for model selection, scalability, and production readiness
Lead design and scaling of intelligent process automation using RPA platforms
Drive automation ROI analysis and establish engineering standards
Design and govern ETL and feature engineering pipelines
Integrate AI and automation systems into enterprise architecture via REST APIs and microservices
Drive adoption of containerization and CI/CD best practices
Architect and implement LLM-powered and agentic AI applications
Define technical approach for integrating LLMs into clinical workflows
Own performance, reliability, and scalability of AI systems
Define alerting, testing, and tuning frameworks
Mentor engineers and shape AI engineering culture
Contribute to hiring and technical interviews

5-8 years of professional software engineering experience with AI/ML focus
Proven track record of delivering production-grade AI/ML systems
Experience with full AI/ML model lifecycle at scale
Experience in regulated industry with compliance and security knowledge
Experience architecting automation solutions with RPA and orchestration tools
Bachelor's degree in Computer Science, Engineering, Mathematics, or related field
Advanced proficiency with Python and ML frameworks
Hands-on experience with cloud AI/ML platforms (AWS SageMaker, Azure AI, or Google Vertex AI)
Expert-level Python with PyTorch, TensorFlow, scikit-learn, and Hugging Face Transformers
Experience with RAG pipelines, vector databases, and multi-agent frameworks (LangChain, LangGraph, AutoGen, CrewAI)
Experience with RPA platforms (UiPath, Power Automate, Automation Anywhere) and orchestration tools (Apache Airflow, Prefect, n8n)
Experience with containerization (Docker, Kubernetes) and CI/CD pipelines
Experience with MLOps tooling (MLflow, Kubeflow)
Deep proficiency in SQL and data architecture patterns
Deep working knowledge of HIPAA compliance and data security
Familiarity with healthcare data standards (HL7 FHIR, ICD-10/CPT)

Experience applying AI, NLP, or ML to healthcare data including claims processing, revenue cycle management, prior authorization, medical coding, or clinical text
Knowledge of healthcare data standards including HL7 FHIR, ICD-10/CPT codes, or DICOM
Experience in Medicare Advantage, managed care, or payer environment
Prior experience as informal technical lead, principal engineer, or engineering lead
Master's degree in Computer Science, AI/ML, or related discipline
Formal certification in MLOps, cloud AI platforms, responsible AI, or agentic AI
Certification in RPA platforms (UiPath, Automation Anywhere, or Microsoft Power Automate)
Participation in advanced AI/ML communities, conferences, or open-source contributions
Cloud certification from AWS, Microsoft Azure, or Google Cloud
RPA platform certification

Skills