Full Stack Developer – AI

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Full Stack Development: Develop, maintain, and enhance frontend applications, backend services, APIs, and microservices to support production GenAI solutions.

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Generative AI Integration: Implement and support AI-powered features using Large Language Models (LLMs), RAG pipelines, prompt engineering, and related technologies.

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Production Support and Troubleshooting: Diagnose and resolve complex application and platform issues, perform root cause analysis (RCA), and implement corrective actions to minimize recurring incidents.

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Performance Optimization: Improve application responsiveness, scalability, reliability, and overall performance across production environments.

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Cloud and Infrastructure: Support application deployment and operations on Azure and/or AWS, applying best practices for cloud environments, containerization, and infrastructure management.

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CI/CD and DevOps: Implement and maintain continuous integration and continuous delivery pipelines using tools and practices involving Docker, Kubernetes, and automated deployment workflows.

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Data Management: Develop and maintain database integrations, data ingestion processes, and supporting infrastructure for SQL, NoSQL, and vector database technologies.

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AI Reliability and Quality: Monitor and address GenAI reliability challenges, including hallucinations, model drift, bias, and other factors affecting application quality and user trust.

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Cross-Functional Collaboration: Partner with engineering, support, and platform teams to resolve incidents, deliver application enhancements, and improve operational efficiency.

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Continuous Improvement: Identify opportunities to strengthen application availability, reduce incident recurrence, and improve engineering processes and production support practices.

Requirements

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Full Stack Development: Strong experience in full stack software development, including frontend and backend application engineering.

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Frontend Technologies: Practical experience with React, Angular, and Node.js for building and maintaining modern applications and services.

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Generative AI Expertise: Hands-on experience with LLMs, RAG pipelines, and prompt engineering, along with an understanding of GenAI application architecture.

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AI Lifecycle Knowledge: Familiarity with AI model lifecycle management, integration patterns, and the challenges associated with deploying AI-powered applications in production.

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Cloud Platforms: Experience working with Microsoft Azure and/or AWS cloud environments.

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DevOps and Containerization: Knowledge of CI/CD pipelines, Docker, Kubernetes, and modern software deployment practices.

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Database Technologies: Strong understanding of SQL and NoSQL databases, with familiarity with vector databases and data ingestion frameworks.

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Production Operations: Experience supporting production applications, troubleshooting complex technical issues, conducting root cause analysis, and implementing sustainable fixes.

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AI Quality and Reliability: Awareness of AI-specific risks, including hallucinations, model drift, bias, and reliability challenges.

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Analytical Skills: Strong problem-solving, debugging, and performance optimization capabilities, with a structured approach to technical challenges.

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Communication and Collaboration: Excellent communication skills and the ability to work effectively with cross-functional teams in a fast-paced technical environment.

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Work Approach: A proactive, quality-focused mindset, with the ability to balance application development, operational support, and continuous improvement.

Benefits

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Contract Duration: 12-month contract, with a stated start date of October 26, 2026, and end date of October 26, 2027.

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Compensation: Advertised hourly pay range of $15–$20 per hour .

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Work Location: Hyderabad, Telangana, India, with the opportunity to work remotely across India; the original listing also mentions onsite work as a possible arrangement.

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Technical Exposure: Work with modern Generative AI technologies, including LLMs, RAG pipelines, and prompt engineering.

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Cloud and Engineering Experience: Build practical expertise in Azure and/or AWS, microservices, CI/CD, containerization, and scalable application architecture.

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Production Engineering: Gain experience improving the reliability, performance, and operational stability of real-world AI applications.

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Cross-Functional Collaboration: Work alongside engineering, support, and platform teams to solve complex technical challenges.

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Professional Development: Strengthen your skills in full stack development, AI integration, cloud infrastructure, and production support. How Jobgether works: We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team. We appreciate your interest and wish you the best!  Why Apply Through Jobgether?    Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.     #LI-CL1