Hybrid
Full Time
Job Title: GenAI Engineer (Senior/Lead) Industry: AI/ML, Enterprise Applications, Healthcare (if applicable) Role Summary: We are seeking an experienced GenAI Engineer to integrate LLM APIs, build AI-driven applications, optimize model performance, and deploy AI services at scale. The ideal candidate has expertise in Python-based AI development, LLM orchestration, cloud deployment, and enterprise AI integration. Key Responsibilities: AI Application Development: Build and maintain Python-based AI services using LangChain and CrewAI. Implement RAG-based retrieval and Agentic AI workflows. LLM Integration & Optimization: Integrate OpenAI, Bard, Claude, Azure OpenAI APIs. Optimize API calls using temperature, top-p, max tokens, and reduce hallucinations using embedding-based retrieval (FAISS, Pinecone). Model Evaluation & Performance Tuning: Assess AI models using Model Scoring, fine-tune embeddings, and enhance similarity search for retrieval-augmented applications. API & Microservices Development: Design scalable RESTful API services. Secure AI endpoints using OAuth2, JWT authentication, and API rate limiting. Cloud Deployment & Orchestration: Deploy AI-powered applications using AWS Lambda, Kubernetes, Docker, CI/CD pipelines. Implement LangChain for AI workflow automation. Agile Development & Innovation: Work in Scrum teams, estimate tasks accurately, and contribute to incremental AI feature releases. Tech Stack & Tools: AI/ML: PyTorch, TensorFlow, Hugging Face, Pinecone LLMs & APIs: OpenAI, LangChain, CrewAI Cloud & DevOps: AWS, Azure, Kubernetes, Docker, CI/CD Security & Compliance: OAuth2, JWT, HIPAA Preferred Qualifications: Experience with AI/ML, LLM integrations, and enterprise cloud solutions. Proven expertise in GenAI API orchestration, prompt engineering, and embedding retrieval. Strong knowledge of scalable AI architectures and security best practices. Notice Period - immediate to 45 days
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