Full-Stack Generative AI Developer

Overview
Seeking talented Full-Stack Generative AI Developer who will design implement and maintain cutting-edge AI-powered applications and this role developer will bridge the gap between advanced generative AI models and user-facing applications creating intuitive interfaces for complex AI capabilities while ensuring robust scalable and efficient backend systems.
Key Responsibilities
AI Development
Design and implement generative AI features leveraging models like GPT-4 Llama or other foundational models Fine-tune and optimize AI models for specific use cases and domains (optional good to have)
Create prompt engineering frameworks and templates to ensure consistent AI behavior
Develop retrieval-augmented generation (RAG) systems that combine vector databases with LLMs
Frontend Development
Build responsive accessible web interfaces for AI-powered applications using modern frameworks (React Vue Angular MUI)
Design intuitive UIs that make complex AI capabilities understandable and usable
Implement real-time features for AI interactions (streaming responses progressive rendering)
Develop visualization components for AI outputs and confidence metrics
Backend Development
Create robust APIs and services to interface with AI models and external services
Design scalable architectures that can handle high-throughput AI inference
Implement efficient data processing pipelines for AI training and inference
Integrate with vector databases document stores and other AI-specific infrastructure
DevOps & MLOps
Set up CI/CD pipelines for AI application deployment
Implement monitoring logging and alerting for AI systems
Optimize infrastructure for cost-effective AI deployment
Required Skills & Experience
Technical Skills
3 years of full-stack development experience (JavaScript/TypeScript Python(must))
1 years working with AI/ML technologies particularly generative AI
Experience with at least one major LLM framework (LangChain Langgraph)
Proficiency with vector databases (Pinecone Mongo FAISS etc.)
Strong understanding of REST APIs GraphQL and microservices architecture (Optional Good to have)
Experience with Git Github actions cloud platforms (AWS Azure GCP) and containerization (Docker Kubernetes)
AI-Specific Knowledge
Deep understanding of LLMs including their capabilities and limitations
Experience with prompt engineering and RAG architecture
Knowledge of embedding models and vector similarity search
Understanding of AI evaluation metrics and testing methodologies
Preferred Qualifications
Experience developing commercial AI applications or products
Knowledge of AI safety practices and responsible AI deployment
Background in NLP computer vision or other AI specialties
Experience with streaming architectures for real-time AI applications
Education
Bachelors degree or higher in Computer Science Software Engineering AI/ML or related field
Relevant certifications in cloud platforms AI frameworks or software development
Personal Attributes
Strong problem-solving skills with a creative approach to AI challenges
Excellent communication skills to explain complex AI concepts to stakeholders
Ability to stay current with rapidly evolving AI technologies and best practices
Self-motivated with the ability to work independently and in cross-functional teams
Keen interest in the ethical implications of AI technology