Agentic AI AWS
An Agentic AI AWS Lead Developer is a senior engineering role responsible for leading the design, development, and deployment of autonomous AI agents on the Amazon Web Services (AWS) cloud platform. This role combines strong software engineering practices, deep AWS expertise, and specialized knowledge of agentic AI frameworks to create scalable, reliable, and secure AI solutions.
Key Responsibilities Lead AI Development: Drive the strategic direction and technical implementation of agentic AI projects, from concept through deployment.
Architecture & Design: Architect and implement scalable, high-performance, and secure AI/ML infrastructures and application stacks on AWS. This includes designing agent roles, memory systems, and inter-agent communication protocols.
AWS Integration: Develop innovative solutions using a wide range of AWS services, such as ECS, EC2, S3, Lambda, DynamoDB, API Gateway, and Amazon Bedrock, ensuring seamless integration into existing systems Coding & Quality Assurance: Write and review high-quality, production-ready code, primarily in languages like Python or Java/Node.js. Ensure adherence to best practices and coding standards.
Collaboration & Mentorship: Work closely with business stakeholders, product managers, data scientists, and engineering teams to understand requirements and deliver valuable solutions. Mentor junior engineers and foster a culture of continuous learning.
Innovation & R&D: Stay ahead of industry trends in agentic AI and generative AI technologies, evaluating new methodologies and tools (e.g., LangChain, PyTorch) to enhance AI capabilities and solve complex business problems.
Required Qualifications & Skills Experience: Proven experience in a senior or lead engineering role, with substantial applied experience in software development (typically 5+ years).
AWS Expertise: Deep understanding of core AWS services and cloud-native application design, including infrastructure-as-code tools like Terraform or CloudFormation. Programming Languages: Strong proficiency in Python, Java, or Node.js.
AI/ML Knowledge: Experience with Agentic AI technologies, LLMs, machine learning algorithms, and relevant libraries/tools (e.g., LangChain, PyTorch, scikit-learn).
Methodologies: Advanced understanding of Agile methodologies, DevOps practices, CI/CD pipelines, and application security principles.
An Agentic AI AWS Lead Developer is a senior engineering role responsible for leading the design, development, and deployment of autonomous AI agents on the Amazon Web Services (AWS) cloud platform. This role combines strong software engineering practices, deep AWS expertise, and specialized knowledge of agentic AI frameworks to create scalable, reliable, and secure AI solutions.
Key Responsibilities Lead AI Development: Drive the strategic direction and technical implementation of agentic AI projects, from concept through deployment.
Architecture & Design: Architect and implement scalable, high-performance, and secure AI/ML infrastructures and application stacks on AWS. This includes designing agent roles, memory systems, and inter-agent communication protocols.
AWS Integration: Develop innovative solutions using a wide range of AWS services, such as ECS, EC2, S3, Lambda, DynamoDB, API Gateway, and Amazon Bedrock, ensuring seamless integration into existing systems Coding & Quality Assurance: Write and review high-quality, production-ready code, primarily in languages like Python or Java/Node.js. Ensure adherence to best practices and coding standards.
Collaboration & Mentorship: Work closely with business stakeholders, product managers, data scientists, and engineering teams to understand requirements and deliver valuable solutions. Mentor junior engineers and foster a culture of continuous learning.
Innovation & R&D: Stay ahead of industry trends in agentic AI and generative AI technologies, evaluating new methodologies and tools (e.g., LangChain, PyTorch) to enhance AI capabilities and solve complex business problems.
Required Qualifications & Skills Experience: Proven experience in a senior or lead engineering role, with substantial applied experience in software development (typically 5+ years).
AWS Expertise: Deep understanding of core AWS services and cloud-native application design, including infrastructure-as-code tools like Terraform or CloudFormation. Programming Languages: Strong proficiency in Python, Java, or Node.js.
AI/ML Knowledge: Experience with Agentic AI technologies, LLMs, machine learning algorithms, and relevant libraries/tools (e.g., LangChain, PyTorch, scikit-learn).
Methodologies: Advanced understanding of Agile methodologies, DevOps practices, CI/CD pipelines, and application security principles.