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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Generative AI Engineer / AI Agent Builder - **Company:** Logicplanet, Inc. - **Location:** Malvern, PA, United States - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Amazon S3, Cloud Engineering, Databases, Continuous Integration, Document Retrieval, Amazon DynamoDB, Identity and Access Management, Python (Programming Language), Search Technologies, Software Engineering, Enterprise Software Applications, Retrieval-Augmented Generation, Large Language Models, Multi-Agent Systems, Prompt Engineering, Kubernetes, Information Technology, Virtual Agents, Functional Programming, Api Gateway, Restful APIs, Docker, Microservices - **Published:** September 25, 2026 - **Apply:** https://www.dice.com/job-detail/81bc0d59-726d-4c8b-940a-b9ceae17354e ## About the Role * Strong hands-on experience with AWS Bedrock. * Strong experience with LangChain and Lang Graph. * Hands-on experience building AI Agents / Agentic AI applications. * Experience with Claude / Anthropic models and Claude Code. * Strong Python programming skills. * Experience with RAG, embeddings, vector databases, and semantic search. * Experience with LLM tool/function calling and agent orchestration. * Knowledge of REST APIs, microservices, and cloud-native application development. * Experience with AWS services such as Lambda, API Gateway, S3, ECS/EKS, DynamoDB, OpenSearch, and IAM. * Experience with prompt engineering, LLM evaluation, and GenAI application optimization. Preferred Skills * Experience with Amazon Bedrock Agents / Agent Core and enterprise agent architectures. * Experience with multi-agent orchestration. * Knowledge of MCP (Model Context Protocol). * Experience with vector databases such as OpenSearch, Pinecone, We aviate, or Chroma. * Experience with CI/CD, Docker, Kubernetes, and AWS DevOps. * Familiarity with AI security, guardrails, observability, and responsible AI. * Experience integrating GenAI solutions with enterprise systems., * Bachelor's or master's degree in computer science, Engineering, or a related field. * 5+ years of software engineering experience, with 2+ years of hands-on GenAI/LLM experience. * Proven experience delivering production-grade AI agents or LLM applications. ## Description * Design and develop AI agents, multi-agent systems, and LLM-powered applications using AWS Bedrock. * Build agentic workflows using Lang Graph and LangChain. * Develop and integrate Claude-based applications, including hands-on experience with Claude Code. * Create autonomous agents capable of tool use, reasoning, planning, orchestration, and workflow execution. * Integrate LLMs with enterprise APIs, databases, applications, and external tools. * Implement RAG (Retrieval-Augmented Generation) pipelines using embeddings, vector databases, document retrieval, and knowledge bases. * Work with AWS Bedrock foundation models, particularly Claude and other supported LLMs. * Develop prompt templates, structured outputs, function/tool calling, and context-management strategies. * Build scalable and secure GenAI solutions using AWS cloud services. * Implement agent memory, state management, workflow persistence, and human-in-the-loop capabilities. * Develop APIs and microservices to expose AI/agent capabilities to enterprise applications. * Perform testing, evaluation, monitoring, and optimization of LLM applications for accuracy, latency, reliability, and cost. * Follow responsible AI, security, privacy, and governance best practices. ## Related Videos - [Docker Compose: Rediscovered](https://www.wearedevelopers.com/videos/1978-docker-compose-rediscovered) - [WeAreDevelopers LIVE - CSS is DOOMed](https://www.wearedevelopers.com/videos/1838-wearedevelopers-live-css-is-doomed) - [Kubernetes and Microservices with Multi-Model Databases](https://www.wearedevelopers.com/videos/382-kubernetes-and-microservices-with-multi-model-databases) - [Building AI Applications with LangChain and Node.js](https://www.wearedevelopers.com/videos/1512-building-ai-applications-with-langchain-and-node-js) - [Docker build without Docker](https://www.wearedevelopers.com/videos/100114-docker-build-without-docker) - [Beyond Chatbots: How to build Agentic AI systems](https://www.wearedevelopers.com/videos/1629-beyond-chatbots-how-to-build-agentic-ai-systems) ## Related Articles - [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models) - [From Prototype to Production: Build AI Agents with This Free 4-Course Learning Path](https://www.wearedevelopers.com/magazine/655-from-prototype-to-production-build-ai-agents-with-this-free-4-course-learning-path) - [Graph and AI Trends 2026: Why Is AI Running but Not Yet Delivering?](https://www.wearedevelopers.com/magazine/680-graph-and-ai-trends-2026-why-is-ai-running-but-not-yet-delivering) - [What is Agentic Programming and Why Should Developers Care?](https://www.wearedevelopers.com/magazine/625-what-is-agentic-programming-and-why-should-developers-care) - [Everything a Developer Needs to Know About MCP with Neo4j](https://www.wearedevelopers.com/magazine/604-everything-a-developer-needs-to-know-about-mcp-with-neo4j) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer)