AI Engineer

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.
  
  

• 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.
  
  

• 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.
  
  

• 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.
  
  

• 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.