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Senior Full Stack Engineer (AI Specialist)
Location
United States
Posted
133 days ago
Salary
75 - 85 / hour
Seniority
Senior
Job Description
Senior Full Stack Engineer (AI Specialist)
Zealogics.com
This description is a summary of our understanding of the job description. Click on 'Apply' button to find out more. Role Description We are seeking a seasoned Full Stack Engineer with advanced AI expertise to architect and deliver enterprise-scale solutions. The role demands deep technical knowledge of AI APIs across OpenAI, Azure, AWS, and Google Cloud, combined with leadership and communication skills to drive innovation and compliance. - Architect, design, and implement scalable full stack applications with integrated AI/ML capabilities. - Lead technical teams, mentor junior engineers, and establish best practices in AI-driven development. - Design and optimize API integrations with OpenAI, Azure Cognitive Services, AWS AI/ML stack, and Google Vertex AI. - Collaborate with stakeholders to align AI solutions with business goals and compliance standards. - Ensure robust monitoring, logging, and governance of AI API usage. - Evaluate emerging AI APIs and frameworks for adoption in enterprise projects. Qualifications - Full Stack Development: React/Angular, Node.js, .NET Core, Python, Java. - AI/ML Expertise: Hands-on with OpenAI APIs (ChatGPT, embeddings, fine-tuning), Azure AI (Cognitive Services, OpenAI Service), AWS AI (SageMaker, Comprehend, Rekognition), Google AI (Vertex AI, Dialogflow). - Cloud & Data: Azure/AWS/GCP proficiency, microservices, APIs, SQL/NoSQL databases. - Leadership: Proven ability to lead teams and manage enterprise-scale delivery. - Soft Skills: Excellent communication, stakeholder engagement, and documentation.
Job Requirements
- Full Stack Development: React/Angular, Node.js, .NET Core, Python, Java.
- AI/ML Expertise: Hands-on with OpenAI APIs (ChatGPT, embeddings, fine-tuning), Azure AI (Cognitive Services, OpenAI Service), AWS AI (SageMaker, Comprehend, Rekognition), Google AI (Vertex AI, Dialogflow).
- Cloud & Data: Azure/AWS/GCP proficiency, microservices, APIs, SQL/NoSQL databases.
- Leadership: Proven ability to lead teams and manage enterprise-scale delivery.
- Soft Skills: Excellent communication, stakeholder engagement, and documentation.
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