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.

  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.