Full Stack Technical Architect

As a Hands-On Full-Stack Technology Architect with expertise in AI and Large Language Models (LLMs), your role involves architecting and building scalable, intelligent, cloud-native systems. You will blend modern full-stack engineering with deep experience in LLMs including platforms like OpenAI, Claude, Mistral, Cohere, and custom models using platforms like Hugging Face, AWS Bedrock, or Vertex AI. Your responsibilities will include: - **Architecture & Design:** - Define scalable, cloud-native architectures for AI and LLM-driven platforms. - Architect complex AI/LLM systems and distributed platforms. - Produce architecture documentation including component diagrams and API contracts. - Apply modern architecture patterns like microservices, event-driven, and composable patterns. - Design environments integrating LLM APIs across microservices and UI layers. - **Hands-On Development:** - Build reusable components, LLM-enabled APIs, and stateful orchestration workflows. - Develop Proof-of-Concepts and reference implementations for LLM-backed capabilities. - Write high-quality code across frontend and backend using languages like Python, Node.js, Java, and Go. - Contribute to CI/CD automation, DevOps workflows, and Infrastructure as Code. - **Frontend Engineering:** - Architect responsive frontends with scalable state management. - Integrate RESTful and GraphQL APIs with attention to security and performance. - Define and enforce frontend coding standards and reusable component patterns. - **LLM Engineering & Integration:** - Integrate LLMs using platforms like OpenAI, Claude, Mistral, Cohere, Vertex AI, etc. - Apply advanced LLM techniques like prompt engineering, embeddings, and finetuning. - Build semantic search and vector DB pipelines using tools like Pinecone, FAISS, etc. - Collaborate with data science and MLOps teams to productionize custom LLMs securely. - **Team Collaboration & Leadership:** - Work closely with cross-functional teams including product, UX/UI, QA, and business units. - Mentor engineers through design reviews and architecture sessions. - Participate in sprint planning, estimation, and decision-making. - Drive architectural collaboration between business units and engineering teams. - Communicate complex technical topics effectively to both technical and non-technical audiences. **Required Skills & Qualifications:** - **Engineering & Architecture:** - Strong hands-on experience in designing scalable, distributed platforms. - Proficiency in JavaScript/TypeScript, Python, or Go. - Frontend experience with React or Angular. - Expertise in microservices architecture and distributed systems. - **Cloud, DevOps & Infrastructure:** - Strong experience with AWS or Azure cloud platforms. - Proficiency in Docker, Kubernetes, Terraform, Helm, CloudFormation. - Experience delivering production-ready systems with attention to scaling and resiliency. - **LLM & AI Platforms:** - Experience integrating LLM APIs and exposure to related technologies. - Proficiency with embeddings, vector databases, and AI/ML platforms. - Understanding of LLM productionization, governance, and best practices. As a Hands-On Full-Stack Technology Architect with expertise in AI and Large Language Models (LLMs), your role involves architecting and building scalable, intelligent, cloud-native systems. You will blend modern full-stack engineering with deep experience in LLMs including platforms like OpenAI, Claude, Mistral, Cohere, and custom models using platforms like Hugging Face, AWS Bedrock, or Vertex AI. Your responsibilities will include: - **Architecture & Design:** - Define scalable, cloud-native architectures for AI and LLM-driven platforms. - Architect complex AI/LLM systems and distributed platforms. - Produce architecture documentation including component diagrams and API contracts. - Apply modern architecture patterns like microservices, event-driven, and composable patterns. - Design environments integrating LLM APIs across microservices and UI layers. - **Hands-On Development:** - Build reusable components, LLM-enabled APIs, and stateful orchestration workflows. - Develop Proof-of-Concepts and reference implementations for LLM-backed capabilities. - Write high-quality code across frontend and backend using languages like Python, Node.js, Java, and Go. - Contribute to CI/CD automation, DevOps workflows, and Infrastructure as Code. - **Frontend Engineering:** - Architect responsive frontends with scalable state management. - Integrate RESTful and GraphQL APIs with attention to security and performance. - Define and enforce frontend coding standards and reusable component patterns. - **LLM Engineering & Integration:** - Integrate LLMs using platforms like OpenAI, Claude, Mistral, Cohere, Vertex AI, etc. - Apply advanced LLM techniques like prompt engineering, embeddings, and finetuning. - Build semantic search and