Principal AI Engineer at TENEX designing and optimizing scalable AI systems for cybersecurity solutions and mentoring teams in a hybrid workplace.
About the role
- AI Architect leading development of AI/ML solutions for healthcare and biotech. Engaging with generative AI, MLOps, and cloud integrations in a collaborative environment.
Responsibilities
- Architect and implement transformer-based generative models tailored for biomedical data, optimizing training pipelines for domain-specific nuances.
- Compare and evaluate generative models (GANs, VAEs, Diffusion Models) for synthetic medical image generation, selecting the most suitable based on use case.
- Design scalable GenAI systems for generating synthetic patient records with built-in HIPAA compliance and data anonymization.
- Fine-tune pre-trained LLMs for domain-specific applications such as drug discovery, clinical trial summarization, and medical literature analysis.
- Develop strategies to mitigate hallucinations in LLMs, especially for clinical decision support systems.
- Design GenAI-powered platforms that integrate seamlessly with existing EHR systems, supporting real-time inference and secure data exchange.
- Define and implement APIs for GenAI services optimized for multi-cloud and hybrid environments, ensuring scalability and interoperability.
- Ensure robust model versioning, traceability, and reproducibility in compliance with regulatory standards.
- Lead the development of CI/CD pipelines and MLOps workflows for model training, evaluation, and deployment.
- Collaborate with data scientists and engineers to optimize model performance using TensorFlow, PyTorch, and Hugging Face.
- Manage cloud-native microservices using Python, FastAPI, and container orchestration tools (e.g., Kubernetes).
Requirements
- Minimum of 10 years of experience in design, development, and deployment.
- Strong foundation in AI/ML, deep learning, and GenAI architectures.
- Hands-on experience with LLMs, RAG systems, LangChain, LangGraph, and vector databases.
- Proficiency in Python, FastAPI, and cloud platforms (AWS, Azure, GCP).
- Experience with MLOps tools and practices (MLflow, Kubeflow, CI/CD).
- Deep understanding of healthcare data standards (FHIR, HL7) and compliance frameworks (HIPAA, GDPR).
- Excellent communication and leadership skills.
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Principal AI Engineer designing and optimizing AI systems at TENEX for advanced cybersecurity solutions. Mentoring teams and driving technical innovation in a hybrid setup.
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