GCP AI Engineer

Lumeris, Inc
Cambridge, MA, United States
3 days ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Experienced
Experience required
4 years minimum
Compensation
$143,190.0 - $194,468.0
Working hours
Regular working hours
Job source

Tech stack

Application Programming Interfaces (APIs) Artificial Intelligence Big Data BigQuery Health Informatics Cloud Computing Information Engineering DevOps Data Flow Control Monitoring of Systems Identity and Access Management Python (Programming Language)
+19 more
Machine Learning Tensorflow Software Deployment Google Cloud Fast Healthcare Interoperability Resources Electronic Medical Records Generative AI Build Server Amazon Virtual Private Cloud (VPC) Containerization Kubernetes Information Technology Health Level Seven International Machine Learning Operations Virtual Agents Terraform Looker Analytics Data Pipelines Docker

Job description

Lead the design, development, and deployment of AI solutions on Google Cloud that elevate patient care and streamline healthcare operations. This role is for engineers who ship end-to-end. You will own problems from definition through production-using AI as a core part of your workflow, not an occasional tool. Your work spans data engineering, model building, and AI Ops, delivering intelligent, production-ready healthcare applications and agents used by clinicians, care teams, and patients., End to End Ownership

  • Own features from problem framing through production deployment and iteration.

  • Work with clinical, product, and engineering partners to define the right problem before building the solution.

  • Stay accountable for outcomes after launch, including performance, reliability, and usability in real-world healthcare settings.

HandsOn Agentic & Generative AI Development

  • Build, troubleshoot, and optimize agentic AI systems using Python, LangChain, LangGraph, and Gemini APIs on Google Cloud.

  • Embed AI agents directly into clinical workflows and user-facing applications, not just prototypes.

  • Design and deploy RAG-based and conversational AI systems that are accurate, grounded, and trustworthy.

AI Ops / ML Ops Implementation

  • Design and automate end to end ML pipelines covering training, validation, deployment, monitoring, and updates.

  • Use Vertex AI, Kubeflow, Cloud Build, Terraform, and related tooling to ensure models are reproducible, observable, and reliable.

  • Monitor production systems, detect drift, and iterate-treating “merge” as the beginning, not the end.

Healthcare Data Engineering

  • Construct secure, compliant data pipelines integrating EHR, FHIR, and HL7 data formats.

  • Support interoperability with EMR systems such as EPIC.

  • Implement validation and quality checks appropriate for regulated healthcare environments.

Develop & Deploy AI/ML Models

  • Build, test, and deploy models supporting:

  • Clinical decision support

  • Patient and clinician interaction

  • Workflow automation

  • Leverage Vertex AI, BigQuery, Dataflow, and Looker for scalable analytics and deployment.

Operational Reliability

  • Use GCP Cloud Operations (Stackdriver) for monitoring, alerting, and troubleshooting.

  • Rapidly diagnose and resolve production issues in distributed AI systems.

  • Continuously optimize for performance, cost, and reliability.

Security & Compliance

  • Apply best practices for IAM, VPC configuration, encryption, and secure access.

  • Ensure compliance with HIPAA and healthcare data privacy standards.

Collaboration & Support

  • Collaborate closely with clinical, product, and IT teams to translate complex needs into working AI solutions.

  • Provide documentation, knowledge sharing, and hands on support for deployed systems.

Requirements

  • Bachelor’s or Master’s degree in Computer Science, Engineering, AI, Health Informatics, or related field.

  • 4+ years of experience building or supporting production software or AI/ML systems, including meaningful exposure to Google Cloud.

  • Experience with Python and modern AI/ML frameworks.

  • Familiarity with containerized deployments (Docker, Kubernetes) and cloud-native systems.

  • Experience contributing to or supporting ML pipelines, model monitoring, or AI-enabled services.

  • Interest in or exposure to healthcare data or regulated environments.

Preferred / Nice to Have

  • Experience with Vertex AI, Kubeflow, or GCP-based ML workflows.

  • Exposure to FHIR, HL7, or EMR systems (including EPIC).

  • Experience building agentic AI, RAG systems, or conversational AI.

  • Background in MLOps, model monitoring, or AI operations.

  • Google Cloud certifications (AI Engineer, DevOps, Cloud Architect).

Benefits & conditions

$143,190.00-$194,467.50

Benefits of working at Lumeris

  • Medical, Vision and Dental Plans
  • Tax-Advantage Savings Accounts (FSA & HSA)
  • Life Insurance and Disability Insurance
  • Paid Time Off (PTO, Sick Time, Paid Leave, Volunteer & Wellness Days)
  • Employee Assistance Program
  • 401k with company match
  • Employee Resource Groups
  • Employee Discount Program
  • Learning and Development Opportunities
  • And much more…

Be part of a team that is changing healthcare!

About the company

At Lumeris, we believe that our greatest achievements are made possible by the talent and commitment of our team members. That’s why we are actively seeking talented and collaborative individuals who are passionate about making a difference in the healthcare industry. Join us today as we strive to create a system of care that every doctor wants for their own family and become part of a community that values its people and empowers you to make an impact.

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