Senior Generative AI Developer
- Gurus Infotech Inc.
3 Days Ago
NA
NA
Jersey City-NJ
11-15 Years
Required Skills: Software development an system design, Python, FastAPI for API Development, Generative AI frameworks and RAG architectures, System and architecture design principles, AWS, Azure, GCP, Vector databases, embedding models, retrieval pipelines, LLM Fine tuning, prompt engineering and model evaluation, Docker and Kubernetes, CI/CD pipelines, DevOps
Job Description
Job Title: Senior Generative AI Developer
Location – Jersey City, NJ- Onsite
Key Responsibilities:
- Architect and develop Generative AI applications using RAG frameworks for enterprise-scale solutions.
- Design and implement robust system architectures for AI-driven platforms ensuring scalability, security, and performance.
- Build and optimize APIs using FastAPI for seamless integration with AI models and data pipelines.
- Collaborate with cross-functional teams to integrate AI solutions into existing systems and workflows.
- Implement data ingestion, preprocessing, and retrieval mechanisms for large-scale knowledge bases.
- Ensure compliance with best practices for cloud deployment (AWS, Azure, or GCP).
- Conduct performance tuning and optimization of AI models and APIs.
- Stay updated with the latest advancements in Generative AI, LLMs, and RAG methodologies.
Required Skills & Qualifications
- 11+ years of professional experience in software development and system design.
- Strong proficiency in Python and experience with FastAPI for API development.
- Hands-on experience with Generative AI frameworks and RAG architectures.
- Solid understanding of system and architecture design principles for distributed applications.
- Experience deploying solutions on any major cloud platform (AWS, Azure, GCP).
- Familiarity with vector databases, embedding models, and retrieval pipelines.
- Strong problem-solving skills and ability to work in a fast-paced environment.
Preferred Qualifications
- Experience with LLM fine-tuning, prompt engineering, and model evaluation.
- Knowledge of containerization (Docker) and orchestration (Kubernetes).
- Exposure to CI/CD pipelines and DevOps practices.
