AI Engineer

Job description

Role Summary We are seeking an experienced AI Engineer to design, develop, and deploy enterprise-grade AI and Agentic AI solutions. The ideal candidate should have strong expertise in AWS Bedrock Agents, AgentCore, LangGraph/LangChain, RAG architectures, vector retrieval systems, and AI-powered data pipelines. The role involves building intelligent agent workflows, AI assistants, Text-to-SQL solutions, and scalable GenAI applications. Key Responsibilities • Design and develop Agentic AI and Generative AI solutions using AWS-native AI services. • Build and orchestrate AI agents using AWS Bedrock Agents and AgentCore . • Develop complex agent workflows using LangGraph and LangChain . • Implement RAG (Retrieval-Augmented Generation) solutions leveraging vector databases, embeddings, reranking, and enterprise knowledge bases. • Design and optimize Text-to-SQL engines for natural language-driven analytics and reporting. • Build scalable AI data pipelines using PySpark, AWS Lambda, and Amazon Redshift . • Implement semantic caching mechanisms to improve AI application performance and reduce inference costs. • Integrate AI solutions with enterprise applications and data platforms. • Collaborate with business and technology stakeholders to define AI use cases and deliver production-ready solutions. • Ensure AI systems are secure, scalable, reliable, and compliant with organizational standards. Mandatory Technical Skills • Strong experience with AWS Bedrock Agents . • Hands-on expertise in AgentCore (AWS-native agent orchestration and action groups). • Experience with LangGraph and LangChain for agent orchestration and workflow management. • Strong understanding of RAG architectures , vector retrieval, embeddings, knowledge bases, and reranking techniques. • Experience developing Text-to-SQL solutions. • Proficiency in Python and AI application development. • Hands-on experience with PySpark, AWS Lambda, and Amazon Redshift . • Experience implementing semantic caching strategies for GenAI applications. • Strong knowledge of REST API integrations and microservices architecture. Good-to-Have Skills • Experience with Multi-Agent Architectures . • Knowledge of Contextual Retrieval techniques. • Experience implementing AI Guardrails and Responsible AI controls. • Knowledge of PII Detection and Data Masking frameworks. • Experience with FastAPI for AI service deployment. • Exposure to enterprise API integrations and AI observability tools. Preferred Qualifications • Bachelor's or Master's degree in Computer Science, Information Technology, Artificial Intelligence, or a related field. • Experience in Banking, Financial Services, or Enterprise Digital Transformation projects. • AWS AI/ML certifications will be an added advantage. Preferred Profile • 4+ years of software engineering experience with at least 2 years of hands-on experience in AI/GenAI development. • Strong problem-solving and analytical skills. • Experience delivering production-grade AI solutions at enterprise scale.