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.

Work arrangement
No