Technical Architect - AI/ML & Clinical Imaging

The ideal candidate will have strong hands-on experience in AWS architecture, AI/ML, MLOps, data engineering, healthcare/clinical imaging integrations, Generative AI, and regulated environments. The candidate should be comfortable working across cloud infrastructure, machine learning platforms, data pipelines, healthcare interoperability, security, and software validation.

Required Technical Skills

AWS Cloud Architecture

• Strong hands-on experience architecting solutions using AWS services.
• Experience with AWS compute, storage, networking, IAM, API management, containers, serverless, monitoring, and data services.
• Strong knowledge of services such as S3, Lambda, Glue, Step Functions, API Gateway, IAM, VPC, CloudWatch, and EKS.

AI/ML & MLOps

• Deep understanding of the complete AI/ML lifecycle and MLOps.
• Experience with model development, experiment tracking, model registry, CI/CD for ML, deployment, monitoring, retraining, and rollback.
• Hands-on experience with Amazon SageMaker, MLflow, Kubeflow, Databricks, Python, and Jupyter.
• Experience with Docker, Kubernetes/EKS, Git, and CI/CD tools.

Data Engineering & Data Platforms

• Strong understanding of modern data engineering and cloud data platforms.
• Experience with S3, Glue, Lambda, Step Functions, Kafka/Kinesis, APIs, metadata, data lineage, and data-quality frameworks.
• Ability to design scalable data pipelines supporting AI/ML and clinical applications.

Clinical Imaging & Healthcare

• Experience architecting clinical imaging and healthcare solutions.
• Strong understanding of DICOM and RIS/PACS concepts.
• Experience with REST APIs, event-driven architectures, healthcare integrations, and interoperability patterns.
• Experience integrating clinical/medical imaging systems with cloud-based platforms is highly desirable.

Generative AI & Agentic AI

• Understanding of LLMs and Generative AI architectures.
• Experience with RAG, vector databases, model evaluation, guardrails, and AI governance.
• Understanding of agentic AI architecture and enterprise AI integration patterns.

Security & Compliance

• Strong experience implementing IAM, encryption, audit logging, observability, DevSecOps, and security controls in cloud environments.
• Understanding of security and compliance requirements for healthcare and regulated systems.
• Experience implementing secure and auditable AI/ML platforms.

GxP / SaMD / Validation

• Familiarity with GxP and SaMD validation.
• Understanding of URS/FRS traceability, software development lifecycle controls, release governance, and validated computerized systems.
• Experience working in regulated healthcare or life-sciences environments is preferred.

Preferred Candidate Profile

The ideal candidate will bring a combination of:

AWS Architecture + AI/ML + MLOps + Data Engineering + Clinical Imaging + Healthcare Integration + Generative AI + Security/Compliance

Candidates with experience in healthcare, medical imaging, life sciences, pharmaceutical, or other regulated environments