Artificial Intelligence Engineer

Job Description / Duties & Responsibilities

• Design, develop, and deploy scalable AI/ML and Generative AI solutions using AWS services.
• Build and orchestrate AI agents using Amazon Bedrock Agents / AgentCore and related agentic AI frameworks.
• Develop intelligent workflows leveraging LLMs, RAG architectures, vector databases, and tool integrations.
• Implement AI applications using Model Context Protocol (MCP) for secure and standardized tool/model interaction.
• Integrate foundation models from Amazon Bedrock and third-party providers into enterprise applications.
• Design and optimize prompt engineering strategies, agent memory, and context management.
• Build APIs and microservices to expose AI functionalities to business applications.
• Collaborate with Data Engineering teams to develop data pipelines supporting AI use cases.
• Implement monitoring, logging, governance, and security controls for AI systems.
• Mentor junior AI engineers and contribute to AI engineering standards and best practices.
• Evaluate emerging AI technologies and recommend improvements to the AI platform ecosystem.
• Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Data Science, or a related field.
• 5+ years of experience in AI/ML engineering and production-grade AI solution development.
• Strong hands-on experience with AWS AI/ML ecosystem, including: Amazon Bedrock, SageMaker, Lambda, API Gateway, ECS/EKS, Step Functions, DynamoDB / RDS / S3
• Experience building Agentic AI systems using:Bedrock Agents / AgentCore, Multi-agent orchestration frameworks, Tool calling and workflow automation
• Strong understanding and implementation experience with: MCP (Model Context Protocol), RAG (Retrieval-Augmented Generation), Vector databases, Embedding models, Prompt engineering
• Proficiency in Python and AI frameworks such as: LangChain, LangGraph, LlamaIndex, FastAPI, PyTorch / TensorFlow (preferred)
• Experience deploying scalable AI applications using Docker and Kubernetes.
• Strong understanding of software engineering best practices, CI/CD, and MLOps.
• Experience working with structured and unstructured data processing pipelines.
• Strong analytical, troubleshooting, and communication skills
• To adhere to the Information Security Management policies and procedures.