Principal AI Integration Engineer

2 days ago

Pune, Maharashtra, India IZiel Healthcare Full time ₹ 20,00,000 - ₹ 25,00,000 per year

Position: Principal AI Integration Engineer

Role Overview

Principal AI Integration Engineer
 to serve as a dedicated technical resource for Customer AI program. This individual will lead integration efforts between AI platforms and enterprise IT systems, ensuring robust, secure, and compliant deployment. The role combines advanced hands-on engineering with strategic oversight of integrations, governance, and support processes.

Key Responsibilities

  • Own the end-to-end integration of AI solutions into enterprise and other IT systems.
  • Lead design and implementation of data pipelines, APIs, and middleware supporting AI workflows.
  • Establish governance and compliance frameworks for AI solution deployment (HIPAA, ISO 13485, FDA 21 CFR Part 11).
  • Collaborate with cross-functional stakeholders (AI teams, IT, compliance, and business units) to align solutions with organizational needs.
  • Ensure system reliability, scalability, and long-term maintainability of AI integrations.
  • Prepare and maintain documentation of architectures, workflows, and support processes.

Qualifications

  • Bachelor's or Master's degree in Computer Science, Engineering, or related field.
  • 8+ years of experience in system integration, enterprise IT, or AI/ML deployment, with at least 3 years in a senior/principal capacity.
  • Deep expertise in APIs, middleware, and cloud-based integration platforms.
  • Strong background in AI/ML deployment, data pipelines, and monitoring frameworks.
  • Familiarity with healthcare/medical device compliance (HIPAA, ISO 13485, FDA Part 11).
  • Excellent communication and leadership skills, with ability to collaborate across technical and business stakeholders.

Preferred Skills

  • Proficiency in Python, SQL, and integration frameworks.
  • Experience with healthcare interoperability standards (HL7, FHIR).
  • Hands-on with ServiceNow, JIRA, or other ITSM tools.
  • Knowledge of AI frameworks like PyTorch / Langchain
  • Familiarity with cloud platforms to integrate AI models and deploy solutions.
  • Knowledge of working on Docker / Kubernetes for building scalable distributed systems

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