Quick Overview
Seniority
Mid Senior
Work mode
Hybrid
Location
United States
Posted
2 days ago
MicroservicesAWSAzureDatabricksGoogle CloudStakeholder Management
Job Description
Core skills needed
- 12+ years of full-stack engineering experience with a demonstrated ability to design, build, and scale production-grade applications.
- 10+ years of experience delivering customer-facing technology solutions in consulting, product engineering, or enterprise environments.
- Proven track record of leading end-to-end solution delivery, from architecture and development through deployment and operational support.
- Hands-on experience building scalable data pipelines, APIs, microservices, and modern web applications.
- Experience designing and implementing AI-powered applications using Large Language Models (LLMs), including integration with platforms such as OpenAI, Anthropic, and Google Gemini.
- Strong understanding of Retrieval-Augmented Generation (RAG), AI agents, prompt engineering, model evaluation, and enterprise AI application patterns.
- Proficiency with AI-assisted software development tools, including GitHub Copilot and other developer productivity platforms.
- Hands-on experience developing and deploying cloud-native solutions on AWS, Azure, or Google Cloud Platform.
- Experience implementing CI/CD pipelines, automated testing, infrastructure-as-code, and production deployment best practices.
- Strong understanding of application security, observability, monitoring, and operational excellence in enterprise environments.
- Databricks Data Engineer Professional certification preferred; hands-on Databricks experience is highly desirable.
- Excellent communication, stakeholder management, and consulting skills, with the ability to translate business requirements into scalable technical solutions.
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