About the role
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.