Company Description Murphi.ai is an AI automation platform focused on healthcare workflows across Home Health, Hospice, Home Care, Mental & Behavioral Health, IDD, and Primary & Specialist Care. For more details see: https://Murphi.ai
Role Description
Engineer - DevOps & AI Automation
Location: United States (Prefer East Coast either in NC or PA)
Experience: 0–3 Years
Employment: Full-Time | Entry Level / Early Career
OPT / STEM OPT: Candidates are welcome to apply
Reports To: Global Head – DevOps, Security & Architecture and U.S. AI Platform Lead
About the Role
We are looking for a DevOps & AI Automation Engineer to join our U.S. technology team.
This is a hands-on engineering role with two primary areas of responsibility:
- DevOps & Platform Reliability – managing our GCP/GKE infrastructure and ensuring reliable operation of our production platform.
- AI Platform & Workflow Automation – working with our U.S.-based AI Platform Lead to build, test, deploy, and improve AI-powered healthcare workflows.
The ideal candidate is an early-career engineer who wants to develop expertise at the intersection of Cloud, Kubernetes, DevOps, Generative AI, and Healthcare AI Automation.
Key Responsibilities
DevOps & Platform Operations
- Maintain and monitor our Google Cloud Platform (GCP) and Google Kubernetes Engine (GKE) infrastructure supporting U.S. and India operations.
- Manage Kubernetes workloads, deployments, containers, APIs, configurations, scaling, and production environments.
- Monitor platform health through Grafana, GCP monitoring, logs, metrics, and alerts.
- Troubleshoot production issues across infrastructure, APIs, backend services, networking, and applications.
- Ensure high availability and rapid resolution of issues so customer operations are never stranded because of platform failures.
- Support CI/CD, infrastructure automation, security, backups, disaster recovery, and cloud optimization.
- Perform root-cause analysis and automate recurring DevOps activities.
AI Platform & Healthcare Workflow Automation
- Work closely with the AI Platform Leads to develop and operate AI-powered platform workflows.
- Build and test AI automation for healthcare clinical, administrative, documentation, compliance, and operational workflows.
- Work with LLMs, AI APIs, AI agents, workflow orchestration, document processing, and structured/unstructured healthcare data.
- Develop AI workflow prototypes, simulations, integrations, and production implementations.
- Help deploy and monitor AI workflows in production and improve their accuracy, reliability, latency, scalability, and cost efficiency.
- Integrate AI workflows with backend APIs and healthcare systems.
- Extensively use Codex and other AI-assisted engineering tools for coding, debugging, testing, automation, log analysis, and DevOps operations.
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Required Skills
- Strong foundational knowledge of Google Cloud Platform (GCP) – required.
- Knowledge of Kubernetes/GKE, Docker, Linux, APIs, and cloud infrastructure.
- Familiarity with Grafana, monitoring, logging, and observability.
- Programming/scripting experience in Python, JavaScript/TypeScript, Java, Go, Bash, or similar.
- Understanding of REST APIs, backend services, databases, Git, and CI/CD.
- Interest or hands-on experience with Generative AI, LLMs, AI APIs, agents, and workflow automation.
- Strong troubleshooting and problem-solving skills.
- Ability to take ownership of production issues through resolution.
Key Metrics
Platform Uptime | GKE Health | API Latency & Error Rates | Deployment Success | MTTD | MTTR | Incident Frequency | AI Workflow Reliability | AI Processing Latency | Cloud/AI Cost Efficiency
Qualifications
- Master's degree in Computer Science, Software Engineering, AI/ML, Data Science, Cloud Computing, or related STEM discipline.
- 0–3 years of experience.
- Fresh graduates with strong GCP, Kubernetes, software development, or AI projects are encouraged to apply.
- Internships, academic projects, and hands-on cloud/AI experience will be considered.
- OPT and STEM OPT candidates are welcome to apply.
Growth Opportunity
DevOps → GCP/Kubernetes → Platform Engineering → Generative AI → AI Agents → Healthcare Workflow Automation → AI Platform Architecture
- The ideal candidate enjoys building, automating, troubleshooting, and owning production systems and wants to grow into a strong DevOps + AI Platform Lead Engineer.