JOB SUMMARY

The Python Full Stack - Gen AI Lead/Architect will be responsible for designing, developing, and enhancing AI Assistant capabilities, including conversational AI, intelligent workflows, and enterprise automation solutions. This role will focus on building advanced Generative AI applications using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG) architectures, multi-agent systems, and cloud-native technologies. The ideal candidate will possess strong Python development expertise, experience with modern GenAI frameworks, and a passion for delivering scalable AI-powered solutions that drive business value and user engagement.

KEY RESPONSIBILITIES
• Design, develop, and enhance AI Assistant capabilities, including conversational AI, chatbot solutions, and workflow automation.
• Build and deploy Generative AI applications using Large Language Models (LLMs) and modern AI frameworks.
• Design and implement Retrieval-Augmented Generation (RAG) pipelines to improve response quality, knowledge retrieval, and contextual accuracy.
• Develop and optimize multi-turn conversational experiences with advanced grounding and context-management logic.
• Design and implement agentic AI solutions utilizing multi-agent architectures and orchestration frameworks.
• Integrate vector databases and semantic search technologies to support enterprise knowledge retrieval and AI-powered experiences.
• Develop and maintain APIs and backend services supporting AI applications and integrations.
• Collaborate closely with Product Managers, Software Engineers, Architects, and Business Stakeholders to define and deliver AI-driven solutions.
• Implement observability, monitoring, evaluation, and performance measurement frameworks for AI systems.
• Optimize prompt engineering strategies and evaluate model performance using industry-standard evaluation methodologies.
• Support deployment, monitoring, troubleshooting, and continuous improvement of AI applications in cloud environments.
• Contribute to architecture decisions, technical design reviews, and AI solution best practices.
• Document AI workflows, solution architectures, integration patterns, and technical specifications.
• Stay current with emerging AI technologies, LLM advancements, and industry best practices.

REQUIRED QUALIFICATIONS
• Bachelor's degree in Computer Science, Artificial Intelligence, Data Science, Software Engineering, or a related technical field.
• Strong hands-on experience in Python development.
• Experience building and deploying Generative AI applications using Large Language Models (LLMs).
• Hands-on experience with GenAI frameworks such as LangChain, LlamaIndex, Semantic Kernel, LangGraph, CrewAI, AutoGen, or similar technologies.
• Strong experience designing and implementing Retrieval-Augmented Generation (RAG) architectures.
• Experience working with vector databases and semantic search platforms.
• Experience developing RESTful APIs and backend services.
• Strong understanding of prompt engineering techniques and prompt optimization strategies.
• Experience evaluating AI models using frameworks such as RAGAS or comparable evaluation methodologies.
• Experience designing and implementing multi-agent AI systems and agent orchestration workflows.
• Knowledge of AI observability, monitoring, evaluation, and performance management frameworks.
• Experience working with AWS cloud services and cloud-native development practices.
• Strong analytical, troubleshooting, and problem-solving skills.
• Excellent communication and collaboration skills.

PREFERRED QUALIFICATIONS
• Experience building enterprise AI Assistants, copilots, virtual agents, or conversational AI platforms.
• Experience with Amazon Bedrock, OpenAI, Anthropic Claude, Google Gemini, or other enterprise LLM platforms.
• Familiarity with AI governance, security, and responsible AI practices.
• Experience developing scalable microservices and distributed systems.
• Experience implementing CI/CD pipelines and MLOps practices.
• Familiarity with knowledge graphs, semantic search, and enterprise search platforms.
• Experience working in Agile development environments.
• Experience integrating AI solutions with enterprise applications and business workflows.

CERTIFICATIONS
• AWS Certified Developer - Associate (Preferred).
• AWS Certified Solutions Architect - Associate (Preferred).
• AWS Certified Machine Learning Engineer or AWS Machine Learning Specialty (Preferred).
• Microsoft Azure AI Engineer Associate (Preferred).
• Google Professional Machine Learning Engineer (Preferred).
• Generative AI or Large Language Model certifications are highly desirable.

TECHNICAL SKILLS
• Python
• Large Language Models (LLMs)
• Generative AI (GenAI)
• Retrieval-Augmented Generation (RAG)
• RAGAS
• Vector Databases
• Prompt Engineering
• Multi-Agent Systems
• Semantic Search
• AI Observability
• AI Evaluation Frameworks
• REST APIs
• AWS Cloud Services
• LangChain
• LlamaIndex
• LangGraph
• CrewAI
• AutoGen
• Semantic Kernel

PREFERRED SKILLS
• Angular
• Front-End Development
• Chatbot Development
• Conversational AI
• Workflow Automation
• Knowledge Management Systems
• MLOps
• CI/CD
• Cloud-Native Architecture
• Enterprise AI Platforms

MANDATORY SKILLS
• Strong Python Development
• Generative AI / Large Language Models (LLMs)
• Retrieval-Augmented Generation (RAG)
• Vector Databases
• API Development
• Prompt Engineering
• RAGAS Evaluation Framework
• Multi-Agent Systems
• AI Observability and Evaluation Frameworks
• AWS Cloud Experience
• Angular Exposure