AI Architect
Exp : 12 to 16 Years
Job Summary:
Experience- 12 to 16 Years
Job Responsibilities
- Design, implement and fine-tune large language models (LLMs) & generative AI solutions using frameworks like OpenAI, Anthropic Claude, Gemini, or open-source models
- Build and optimize RAG (Retrieval-Augmented Generation) pipelines, vector databases, and prompt engineering strategies for enhanced AI responses
- Develop AI-powered applications integrating LLMs with APIs, agents, and workflows to solve business use cases
- Deploy and monitor generative AI models in production environments, ensuring performance, scalability, and responsible AI practices
- Collaborate with cross-functional teams to translate business requirements into GenAI solutions and stay current with emerging trends in generative AI
- Implement guardrails, evaluation frameworks, and testing protocols to ensure output quality, safety, and compliance with ethical AI standards
- Experience in utilizing generative AI models (e.g., GPT, Gemini, Claude) to solve business challenges and deliver innovative solutions.
- Drive innovation by exploring new advancements in Generative AI and vector database technology.
- Guide and mentor junior engineers on AI development, coding standards, and best practices.
- Participate in code reviews, design discussions, and sprint planning to ensure quality and alignment with project goals.
Essential Qualifications and Skills
- Bachelor’s or Master’s degree in computer science, Engineering or a related field.
- 12+ years of experience in software development, with strong proficiency in Python (preferred for AI/ML workflows).
- 2+ years of hands-on experience in Generative AI, including working with LLMs, embeddings, vector databases, prompt engineering, and GenAI frameworks.
- Rich experience in Agentic AI (e.g., LangGraph, AutoGen, ReAct-based agents, multi-agent orchestration)Working experience in any Agentic AI framework (e.g. LangGraph , crew AI)
- Strong experience with GenAI frameworks (LangChain, LlamaIndex, Haystack) and LLM APIs (OpenAI, Anthropic, Azure OpenAI)
- Expertise in prompt engineering, fine-tuning techniques and working with vector databases (Pinecone, opensearch, ChromaDB, FAISS)
- Solid understanding of transformer architectures, attention mechanism etc.
- Hands-on experience deploying AI applications using cloud platforms (AWS, Azure, GCP) and containerization tools (Docker, Kubernetes)
- Knowledge of MLOps practices, evaluation metrics for LLMs, and implementing responsible AI principles including bias mitigation and safety guardrails
- Develop and maintain REST APIs for seamless integration of AI solutions with enterprise systems.
Desirable Qualifications and Skills
- Experience in the Insurtech or Fintech domain.
- Knowledge of policy administration systems or insurance industry workflows.
- Experience in application development technologies like Java, Spring boot will be added advantage.