Job Description Summary

Job Description

Key Responsibilities

AI Platform & Solution Architecture

• Design and build scalable multi-tenant AI platforms on AWS supporting diverse ML and GenAI use cases.

• Define reference architectures reusable components and best practices for AI/ML systems.

• Architect end-to-end AI pipelines spanning data ingestion feature engineering model training deployment and monitoring.

• Ensure platform readiness for SaaS environments including tenant isolation scalability and cost optimization.

Machine Learning & Deep Learning Engineering

• Lead development of machine learning and deep learning models for production-grade applications.

• Establish standards for ML engineering including data preprocessing feature stores training pipelines and inference services.

• Optimize model performance scalability and latency for real-time and batch inference systems.

Generative AI & Agentic AI Systems

• Design and implement Generative AI solutions using AWS Bedrock and foundation models.

• Build RAG (Retrieval-Augmented Generation) pipelines with vector databases and embeddings.

• Develop agentic AI systems including autonomous agents orchestration frameworks and tool integration.

• Apply advanced techniques such as prompt engineering fine-tuning evaluation frameworks and guardrails.

AWS Cloud Architecture

• Architect and implement solutions using:

• AWS SageMaker (training pipelines deployment)

• AWS Bedrock (GenAI services)

• Compute: Lambda ECS EKS

• Orchestration: Step Functions

• Storage/Data: S3 Redshift DynamoDB Glue

• Build highly available fault-tolerant and cost-optimized cloud-native systems.

• Implement Infrastructure as Code (IaC) using Terraform AWS CDK or CloudFormation.

MLOps & Model Lifecycle Management

• Establish and scale MLOps frameworks for continuous integration and deployment of ML models.

• Implement MLflow for experiment tracking model registry and lifecycle management.

• Build automated CI/CD pipelines for ML workflows.

• Enable model monitoring drift detection retraining pipelines and explainability.

Data Architecture & Engineering

• Design scalable data architectures to support AI/ML workloads (batch and streaming).

• Implement data pipelines feature stores and data governance frameworks.

• Ensure data quality lineage and accessibility across teams.

Security Compliance & Governance

• Architect AI systems with security-first principles including encryption IAM and network controls.

• Ensure compliance with enterprise and regulatory standards (e.g. HIPAA GDPR SOC2 as applicable).

• Implement responsible AI practices including bias detection auditability and explainability.

• Establish governance for data models and AI services.

SaaS Platform Engineering

• Design and implement AI-powered SaaS platforms supporting:

  • Multi-tenancy and tenant isolation

  • API-driven architectures

  • Usage metering and cost attribution

• Enable platform extensibility and integration with enterprise systems.

Leadership & Collaboration

• Provide technical leadership and mentorship across AI ML and cloud engineering teams.

• Collaborate with product engineering and business stakeholders to translate requirements into scalable solutions.

• Lead architecture reviews design discussions and technical decision-making.

• Drive innovation and adoption of emerging AI paradigms.

Required Qualifications

• Bachelors or Masters degree in Computer Science AI Data Science or related field (PhD preferred) with a minimum of 12 years of experience in software engineering AI/ML and cloud architecture.

• Good expertise in Machine Learning Engineering and Deep Learning Engineering.

• Hands-on experience with:

• AWS (SageMaker Bedrock core cloud services)

• MLflow and MLOps frameworks

• Good programming skills in Python and ML frameworks (PyTorch TensorFlow etc.).

• Proven experience designing and deploying scalable AI systems in production.

• Experience with Infrastructure as Code (Terraform CDK CloudFormation).

• Good understanding of data architecture and distributed systems.

• Experience implementing secure and compliant cloud solutions.

Preferred Qualifications

• Experience with agentic AI frameworks and multi-agent systems.

• Familiarity with LLM orchestration tools (LangChain LlamaIndex).

• Experience with vector databases (Pinecone OpenSearch FAISS).

• Knowledge of streaming and big data technologies (Kafka Spark).

• AWS certifications:

• AWS Certified Solutions Architect Professional.

• AWS Machine Learning Specialty

• Experience in enterprise SaaS platforms or regulated industries.

Key Skills & Competencies

• Expertise in scalable AI system design

• Good foundation in ML DL and GenAI

• Deep knowledge of MLOps and cloud-native architectures

• Excellent problem-solving and system design skills

• Good communication and stakeholder management

• Ability to balance innovation with enterprise constraints (security compliance cost)

Impact of the Role

This role will be instrumental in shaping the organizations AI platform strategy and execution enabling rapid development and deployment of next-generation AI solutions including Generative AI and agentic systems while ensuring scalability security and compliance at enterprise scale.

Inclusion and Diversity

GE Healthcare is an Equal Opportunity Employer where inclusion matters. Employment decisions are made without regard to race color religion national or ethnic origin sex sexual orientation gender identity or expression age disability protected veteran status or other characteristics protected by law.

We expect all employees to live and breathe our behaviors: to act with humility and build trust; lead with transparency; deliver with focus and drive ownership always with unyielding integrity.

Our total rewards are designed to unlock your ambition by giving you the boost and flexibility you need to turn your ideas into world-changing realities. Our salary and benefits are everything youd expect from an organization with global strength and scale and youll be surrounded by career opportunities in a culture that fosters care collaboration and support.

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Additional Information