> Markdown version of [/jobs/ext/2702603-gcp-ai-engineer](https://www.wearedevelopers.com/jobs/ext/2702603-gcp-ai-engineer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # GCP AI Engineer - **Company:** Lumeris, Inc - **Location:** Cambridge, MA, United States (Remote available) - **Experience:** Experienced - **Salary:** $143,190.0 - $194,468.0 - **Contract:** Permanent contract - **Skills:** 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), 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 - **Published:** September 4, 2026 - **Apply:** https://startup.jobs/gcp-ai-engineer-cambridge-ma-lumeris-8415925 ## About the Role * 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). ## 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. ## Related Videos - [Alibaba Big Data and Machine Learning Technology](https://www.wearedevelopers.com/videos/37-alibaba-big-data-and-machine-learning-technology) - [Docker Compose: Rediscovered](https://www.wearedevelopers.com/videos/1978-docker-compose-rediscovered) - [From DevOps to Scaled DevOps: How We’re Rebuilding Continuous Delivery as a Platform](https://www.wearedevelopers.com/videos/100018-from-devops-to-scaled-devops-how-we-re-rebuilding-continuous-delivery-as-a-platform) - [The Cloud is Calling: Answer with In-Demand Skills](https://www.wearedevelopers.com/videos/945-the-cloud-is-calling-answer-with-in-demand-skills) - [Coffee with Developers - Maria Apazoglou](https://www.wearedevelopers.com/videos/1209-coffee-with-developers-maria-apazoglou) - [Docker build without Docker](https://www.wearedevelopers.com/videos/100114-docker-build-without-docker) ## Related Articles - [Got AI ideas but no money? Here are 10 free ways to level up your AI skills with Google Cloud](https://www.wearedevelopers.com/magazine/600-got-ai-ideas-but-no-money-here-are-10-free-ways-to-level-up-your-ai-skills-with-google-cloud) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [7 Cloud Computing Trends Coming in 2025 for Developers](https://www.wearedevelopers.com/magazine/412-7-cloud-computing-trends-coming-in-2025-for-developers) - [MLOps – What’s the deal behind it?](https://www.wearedevelopers.com/magazine/125-mlops-what-s-the-deal-behind-it)