AI Architect

About the Position

We are seeking an experienced AI Architect with 12+ years in software development and 2+ years in Generative AI to design and implement large language models and generative AI solutions.

Responsibilities

• Design, implement, and fine-tune large language models (LLMs) & generative AI solutions using frameworks like OpenAI, Anthropic, 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.
• 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.

Requirements

• 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).
• 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 mechanisms, 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.

Nice to Have

• 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.

We Offer

• Opportunity to work with cutting-edge AI technologies.
• Collaborative and innovative work environment.
• Potential for professional growth and development.

About the Company

[Company description if present]