Architect and deliver enterprise AI platform capabilities including workflow orchestration engines, multi-provider LLM integration, and automated deployment pipelines that enable healthcare teams to build and deploy AI applications at scale
Design multi-tenant infrastructure with automated provisioning, namespace isolation, and role-based access control to support secure, per-team dedicated environments across the platform
Build backend services and APIs for workflow authoring, execution orchestration, and platform observability using cloud-native patterns on Kubernetes infrastructure
Implement production observability and reliability practices including distributed tracing, performance monitoring, and incident response for platform health and cost management
Drive technical architecture decisions across the platform, mentor engineers on design patterns, security best practices, and operational excellence
Partner with business stakeholders, product teams, and engineering leadership to align platform roadmap with healthcare automation objectives and adoption strategy
Champion security posture including secrets management, audit logging, compliance requirements, and production readiness standards

Requirements

7+ overall years of software engineering experience building and delivering production-grade backend services, distributed systems, and platform infrastructure
5+ years of backend development experience with modern programming languages and frameworks (Python, Node.js, or Java) including REST/GraphQL APIs, microservices architecture, and asynchronous processing using message brokers (Kafka or Similar)
3+ years building highly available, scalable backend platform services with cloud-native infrastructure including Kubernetes, containerized deployments, and CI/CD pipelines
2+ years of experience with Google Cloud Platform including Google Kubernetes Engine (GKE), Cloud Storage, and cloud-native service deployment
2+ years of technical leadership including architecture decision-making, design reviews, and mentoring engineers
1+ years with LLM integration, AI application development, or intelligent automation systems including prompt engineering and model orchestration
Experience with agentic AI frameworks and orchestration tools (LangGraph, LangChain, Crew AI, or similar) for building multi-agent systems and workflow automation
Experience building and operating large-scale distributed systems with strong observability practices and telemetry-driven decision making
Strong collaboration and communication skills with proven track record of mentoring engineers and adapting quickly to changing requirements
Multi-tenant platform architecture and role-based access control implementation
Experience with managed AI/ML cloud services, modern JavaScript frameworks, and analytics platforms
Experience working in Agile/Scrum development methodology
Commitment to engineering excellence including code reviews, automated testing, and quality gates
Healthcare domain knowledge or experience building healthcare technology solutions.

Benefits

Affordable medical plan options
401(k) plan (including matching company contributions)
Employee stock purchase plan
No-cost programs for all colleagues including wellness screenings, tobacco cessation and weight management programs, confidential counseling and financial coaching
Benefit solutions that address the different needs and preferences of our colleagues including paid time off, flexible work schedules, family leave, dependent care resources, colleague assistance programs, tuition assistance, retiree medical access and many other benefits depending on eligibility.

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

PythonNode.jsJavaREST APIsGraphQL APIsmicroservices architectureasynchronous processingKubernetesCI/CD pipelinesLLM integration

Soft Skills

collaborationcommunicationmentoringtechnical leadershipadaptabilityarchitecture decision-makingdesign reviewsengineering excellenceincident responseperformance monitoring