GCP AI Engineer - Cambridge, MA
LumerisYour Future is our Future
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.
Position:
GCP AI Engineer - Cambridge, MAPosition Summary:
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.Job Description:
Key Responsibilities
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.
Continuous Learning & Prototyping
Stay current with advances in GCP, agentic AI, and generative AI.
Prototype, test, and validate new AI workflows, moving successful ideas into production.
Required Qualifications
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).
Work Environment
Based in Cambridge, MA
Hybrid schedule with 3 days onsite per week.
Collaborative, growth oriented team that values ownership, clarity, and real world impact.
Pay Transparency:
Factors that may be used to determine your actual pay rate include your specific skills, experience, qualifications, location, and comparison to other employees already in this role. In addition to the base salary, certain roles may qualify for a performance-based incentive and/or equity, with eligibility depending on the position. These rewards are based on a combination of company performance and individual achievements.
The hiring range for this position is:
$143,190.00-$194,467.50Benefits 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!
Member Facing Position:
No- Not Member or Patient Facing PositionLocation:
MassachusettsTime Type:
Full timeLumeris and its partners are committed to protecting our high-risk members & prospects when conducting business in-person. All personnel who interact with at-risk members or prospects are required to have completed, at a minimum, the initial series of an approved COVID-19 vaccine. If this role has been identified as member-facing, proof of vaccination will be required as a condition of employment.
Disclaimer:
The job description describes the general nature and level of work being performed by people assigned to this job and is not intended to be an exhaustive list of all responsibilities, duties and skills required. The physical activities, demands and working conditions represent those an employee encounters while performing the essential functions of this job. Reasonable accommodations may be made to enable individual with disabilities to perform the essential job duties and responsibilities.