- Company Name
- MBN Solutions
- Job Title
- Artificial Intelligence Engineer
- Job Description
-
**Job Title:**
Senior AI Engineer – Healthcare (Agentic AI)
**Role Summary:**
Lead the design, development, and deployment of agentic AI solutions that streamline clinical workflows in healthcare settings. Build secure, scalable, and compliant AI systems integrating with electronic health records and clinical infrastructure.
**Expectations:**
- Minimum 5 years of experience building and shipping production AI or software systems in fast‑paced, startup environments.
- Proven ability to translate complex AI research into reliable, production‑grade code.
- Deep understanding of system design, security, and compliance within regulated healthcare domains.
**Key Responsibilities:**
- Architect and implement AI agents using Python and TypeScript, ensuring high availability and low latency.
- Design microservices and event‑driven pipelines on Azure or GCP.
- Develop and maintain infrastructure-as‑code, Docker containers, and Kubernetes deployments.
- Integrate AI workflows with healthcare data standards (FHIR, HL7, DICOM).
- Implement MLOps practices for model training, versioning, monitoring, and continuous delivery.
- Enforce strict security and compliance measures, including data privacy, encryption, and audit logging.
- Collaborate with data scientists, product managers, and clinical stakeholders to refine AI product features.
**Required Skills:**
- Proficiency in Python and TypeScript.
- Experience with Azure or Google Cloud Platform infrastructure.
- Strong knowledge of distributed systems, microservices, and event‑driven architectures.
- Solid grasp of system design and security principles.
- Practical experience with Docker, Kubernetes, and infrastructure-as‑code tools.
- Familiarity with MLOps tooling (e.g., MLflow, Kubeflow).
- Understanding of healthcare data standards: FHIR, HL7, DICOM (preferred).
**Required Education & Certifications:**
- Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, or related field, or equivalent professional experience.
- Relevant cloud or container certifications (e.g., Azure Solutions Architect, Google Cloud Professional Cloud Architect, Certified Kubernetes Administrator) are advantageous but not mandatory.