Note: The job is a remote job and is open to candidates in USA. Luxoft is seeking a highly experienced Lead AI/ML Engineer to support an enterprise healthcare technology environment. The role focuses on integrating Agentic AI into the software development lifecycle, developing full-stack and cloud-native applications, implementing DevOps practices, troubleshooting production issues, and providing technical leadership within an Agile engineering POD.
Responsibilities
- Design, build, and integrate Agentic AI agents into the software development lifecycle
- Lead and contribute to AI-enabled development within an Agile engineering POD
- Design and develop full-stack applications using React, Java/J2EE, Spring, REST APIs, and microservices
- Develop and support cloud-native solutions across Azure, OpenShift, and AKS
- Implement and maintain CI/CD and DevOps practices using GitHub Actions, Artifactory, and Docker
- Troubleshoot complex application and production issues using Splunk, Azure KQL, Grafana, and Dynatrace
- Actively leverage enterprise-approved AI tools to improve coding, documentation, analysis, and engineering productivity
- Provide technical leadership and promote AI engineering best practices across the team
Skills
- 12+ years of software engineering experience
- Agentic AI
- AIDLC
- Java/J2EE
- Spring
- REST APIs
- Microservices
- React
- JavaScript
- HTML/CSS
- Next.js
- SQL
- GraphQL
- PostgreSQL
- Azure
- OpenShift
- AKS
- GitHub
- GitHub Actions
- Docker
- Artifactory
- Splunk
- Azure KQL
- Grafana
- Dynatrace
- Agile/Scrum
- 12+ years of software engineering/programming experience with strong hands-on expertise in Agentic AI and AI-enabled SDLC/AIDLC practices
- Proven experience building AI agents and working within engineering PODs that leverage AI throughout the development lifecycle
- Strong full-stack development experience with React 16+, Java/J2EE, Spring Core/Boot/Batch, REST APIs, microservices, Next.js, SQL/GraphQL, and PostgreSQL
- Hands-on cloud and DevOps experience with Azure, OpenShift, AKS, GitHub Actions, Artifactory, and Docker
- Strong production troubleshooting and debugging capabilities using Splunk, Azure KQL, Grafana, and Dynatrace
- Candidates are expected to actively use enterprise-approved AI tools such as GitHub Copilot, Microsoft 365 Copilot, and approved GenAI platforms, maintaining 90%+ weekly AI-tool usage and applying AI to coding, documentation, analysis, and decision-making workflows
- Prior healthcare industry experience is preferred, particularly experience with Utilization Management, Prior Authorization, Care Management, or Optum Clinical Manager
- Experience leading or mentoring engineers within Agile PODs and driving enterprise AI adoption is an advantage
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