LLM Agent Engineer

Expedite Commerce
Summary
Join a forward-thinking team reshaping how businesses leverage AI by developing and fine-tuning large language model (LLM) agents. You will craft next-generation LLM agent solutions using AWS technologies like SageMaker, Bedrock, Lambda, Step Functions, DynamoDB, and Kinesis. This role involves designing, building, deploying, and continuously improving LLM agents to tackle real-world challenges. Collaborate with cross-functional teams to integrate LLM agents into AWS-driven infrastructures, fostering innovative approaches to problem-solving. You will utilize cutting-edge generative models and AI-powered IDEs to optimize performance and scalability. Leave a legacy by influencing how people interact with AI and shaping the next wave of agent-based design.
Requirements
- Hands-on experience in developing and deploying LLM agents with advanced features like tool integration, contextual memory systems, and feedback-driven learning using a custom agent framework
- Demonstrated expertise in designing and implementing multi-agent systems, enabling agents to collaborate and solve complex tasks efficiently
- Experience in building robust inter-agent communication protocols to ensure seamless coordination between multiple agents
- Skilled in designing systems for state transfer and context preservation across multiple agents, ensuring consistent and accurate task execution
- Experience leveraging AWS Bedrock and related AWS services to build efficient and scalable solutions
- Familiarity with deploying agents in Docker containerized environments and adhering to best practices
- Keeps up with advancements in LLMs, experimenting with and implementing new techniques to solve real-world challenges
- Thrives in a fast-paced environment by learning new methods and unlearning outdated practices
- Proficient in AWS services such as Lambda, Step Functions, DynamoDB, S3, and Kinesis to build event-driven solution stack
- Experience in maintaining CI/CD pipelines using AWS tools like CodePipeline, CodeBuild, and CodeDeploy
- Experience in monitoring and optimizing deployment costs, with a focus on identifying inefficiencies and implementing resource-saving strategies
- You thrive in an environment that encourages calculated experimentation and embraces occasional failures as opportunities to learn
- You communicate effortlessly with diverse teams and client stakeholders, championing clarity, empathy, and knowledge-sharing
Responsibilities
- Develop and fine-tune large language model (LLM) agents that transform entire businesses
- Craft next-generation LLM agent solutions using AWS technologies like SageMaker, Bedrock, Lambda, Step Functions, DynamoDB, and Kinesis
- Leverage these tools for real-time data insights, enabling seamless inter-agent communication, state transfer, and memory handling
- Collaborate with a team driven by bold risks, creativity, and user-centric innovation
- Shape the future of AI with scalable, serverless, multi-agent systems
- Conceptualize, build, deploy, and continuously improve LLM Agents that tackle real-world challenges and drive measurable outcomes
- Leverage AWS services such as Container, Lambda, and Bedrock to create scalable, serverless solutions, enabling agents to operate with precision and reliability
- Work side-by-side with a forward-thinking leadership team that values experimentation, continuous learning, and radical transparency
- Collaborate with cross-functional teams to integrate LLM agents into AWS-driven infrastructures, fostering innovative approaches to problem-solving while maintaining a customer-first perspective
- Design and deploy LLM Agents that scale across business lines, leveraging AWS tools like API Gateway, Step Functions, and DynamoDB for seamless integration into diverse products, services
- Utilize cutting-edge generative models, AWS AI/ML services, and AI-powered IDEs to develop and deploy LLM Agents, optimizing performance, scalability, and real-time application outcomes
- Influence not just the technology stack, but the very way people interact with AI
- Help craft solutions that endure, shaping the next wave of agent-based design across multiple verticals
Preferred Qualifications
Familiarity with Terraform
Benefits
- Health Insurance
- PTO
- Leave time
- Ongoing paid professional training and certifications
- Fully Remote work Opportunity
- Strong Onboarding & Training program
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