Note: The job is a remote job and is open to candidates in USA. Dice is seeking an AI Engineer to design, develop, deploy, and optimize production-grade artificial intelligence solutions. The role focuses on building full-stack AI applications and scalable services, leveraging Google Cloud Platform, and maintaining CI/CD pipelines while integrating and monitoring AI/ML models in enterprise applications.
Responsibilities
- Design, develop, and implement advanced AI/ML solutions using Python and modern AI frameworks
- Build and integrate AI-powered full-stack applications, including backend services, APIs, and user-facing applications
- Develop scalable AI services and REST APIs using Python, FastAPI, Flask, or similar frameworks
- Leverage Google Cloud Platform (Google Cloud Platform) services to build, deploy, and scale AI/ML applications
- Develop and maintain production-grade CI/CD pipelines for AI and software applications
- Containerize AI applications using Docker and deploy workloads using Kubernetes/Google Cloud Platform services
- Integrate AI/ML models, LLMs, APIs, databases, and external data sources into enterprise applications
- Implement model serving, monitoring, testing, versioning, and continuous improvement practices
- Collaborate with data scientists, software engineers, cloud engineers, and product teams to deliver end-to-end AI solutions
- Apply software engineering best practices including unit testing, code reviews, version control, automation, security, and performance optimization
- Troubleshoot and optimize AI applications for scalability, reliability, latency, and cost
- Stay current with emerging AI technologies, frameworks, cloud services, and engineering best practices
Skills
- * **Artificial Intelligence (AI): Mastery**
- * **Python AI: Advanced**
- * **Full Stack Developer – AI: Advanced**
- * **Google Cloud Platform Engineering: Advanced**
- * **CI/CD Pipeline: Advanced**
- * Strong experience developing production-grade AI/ML applications
- * Strong Python programming and AI/ML framework experience
- * Experience building AI-enabled full-stack applications and APIs
- * Hands-on experience with Google Cloud Platform services and cloud-native architectures
- * Strong understanding of CI/CD, DevOps, Git, automated testing, and deployment pipelines
- * Experience with Docker and Kubernetes is highly preferred
- * Strong understanding of REST APIs, microservices, databases, and distributed systems
- * Excellent problem-solving, communication, and collaboration skills
- * Bachelor''s or Master''s degree in Computer Science, Artificial Intelligence, Machine Learning, Engineering, or a related field
- * **5+ years of software/AI engineering experience**, with significant hands-on experience delivering AI solutions to production
- * Demonstrated experience owning AI projects from **design and development through deployment and production support**
- * Experience with **Generative AI, LLMs, RAG, prompt engineering, or AI agents**
- * Experience with frameworks such as **LangChain, LangGraph, LlamaIndex, PyTorch, TensorFlow, or Hugging Face**
- * Experience with Google Cloud Platform AI services such as **Vertex AI, BigQuery, Cloud Run, GKE, Pub/Sub, and Cloud Storage**
- * Experience implementing **MLOps/LLMOps** practices
- * Familiarity with Terraform or other Infrastructure as Code tools
- * Experience with application monitoring, logging, observability, and model performance monitoring
Benefits
- Remote work arrangement
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