Role: GenAI & Java Lead Engineer with Google Cloud Platform
Location: Minneapolis, MN (Hybrid)
Exp: 12+ years MUST
Primary Skills: GenAI, Google Cloud Platform, AI/ML, Java
Job Description
We are looking for a Lead Software Engineer with strong Full Stack development experience and expertise in Generative AI, AI/ML, and cloud, Java technologies to design, develop, deploy, and support AI-powered enterprise applications
Key Responsibilities
- Design, develop, test, deploy, and support end-to-end AI-powered enterprise applications.
- Build modern frontend applications using React, Angular, TypeScript, HTML5, CSS, and responsive UI frameworks.
- Develop scalable backend services using Java, Spring Boot, .NET, C#, Node.js, Python, and microservices architecture.
- Design and integrate RESTful APIs, GraphQL services, and enterprise integrations.
- Build and optimize database solutions using SQL Server, PostgreSQL, NoSQL, and vector databases.
- Develop GenAI solutions using OpenAI, Azure AI, Gemini, Claude, Semantic Kernel, LangChain, and LangGraph.
- Implement Retrieval-Augmented Generation (RAG), semantic search, embeddings, vector databases, and knowledge retrieval systems.
- Design and develop Agentic AI workflows, autonomous agents, orchestration frameworks, and AI-powered automation.
- Build and deploy cloud-native applications using Azure, AWS, or Google Cloud Platform services, including serverless computing, storage, messaging, and AI services.
- Implement DevOps practices using GitHub, CI/CD pipelines, Docker, Kubernetes, Infrastructure as Code (IaC), monitoring, and automated testing.
- Collaborate with Product Managers, Architects, Data Scientists, Security, Compliance, and Business teams.
- Ensure Responsible AI, security, governance, privacy, compliance, observability, and operational excellence throughout the AI lifecycle.
Required Skills
- Java, Spring Boot, and Full Stack Development
- Generative AI and AI/ML
- Google Cloud Platform (Google Cloud Platform)
- React or Angular, TypeScript, HTML5, and CSS
- REST APIs, GraphQL, and microservices
- RAG, embeddings, semantic search, and vector databases
- Agentic AI and AI orchestration frameworks
- Cloud-native development and DevOps practices
