Agentic AI Developer
5 days ago
Role Description
:
We are seeking an experienced Senior Agentic AI Developer to design and deploy sophisticated agentic AI workflows and applications. This role requires full-stack development expertise, generative AI proficiency, and cloud engineering experience to architect autonomous AI systems using cutting-edge frameworks.
Key Responsibilities:
Design and implement agentic AI workflows using AutoGen, CrewAI, LangChain, or an Agent Development Kit (ADK)
Integrate Model Context Protocol (MCP) for seamless AI-system communication
Develop, test, and refine advanced prompts using systematic engineering methodologies
Build full-stack generative AI applications on AWS Bedrock
Develop Python backend services and React front-end interfaces
Design scalable cloud architectures leveraging AWS services
Implement CI/CD pipelines for AI deployment and monitoring
Required Qualifications
Experience:
8+ years professional technical/software development experience
1-2 years hands-on AI/ML development experience
1+ year production experience with AWS Bedrock and cloud services
2+ years Python programming experience
2+ years Front-end development experience with React
Technical Skills:
Agentic AI Frameworks:
AutoGen, CrewAI, LangChain, or ADK
Model Context Protocol (MCP) implementation
Retrieval-Augmented Generation (RAG) architectures
GenAI & Prompt Engineering:
Advanced prompt design and optimization
Systematic testing and evaluation methodologies
Deep understanding of LLMs and their capabilities
Programming:
Python: Advanced proficiency including async programming, testing frameworks
React: Component development, state management, hooks
RESTful API design and implementation
AWS & Cloud:
Amazon Bedrock (Claude, Titan, Llama models)
Lambda, ECS, S3, DynamoDB
CloudWatch, IAM, security best practices
Infrastructure as Code (CloudFormation/CDK)
Development Practices:
Agile/Scrum, test-driven development
CI/CD pipeline implementation
Code review and documentation
Preferred Qualifications:
Experience with additional frameworks (Semantic Kernel, Haystack, LlamaIndex)
Knowledge of other cloud platforms (Azure OpenAI, Google Vertex AI)
MLOps practices and containerization (Docker, Kubernetes)
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