Why This Role Stands Out
You'll thrive as a Senior Agentic AI Developer by building cutting-edge AI agents and RAG systems, leveraging your expertise in Python and LLM frameworks. This remote, hybrid role offers an excellent hourly rate and the chance to shape enterprise-grade AI solutions, making it ideal for experienced AI developers ready for impactful projects.
Quick Overview
Salary
$85/hr
Seniority
Mid Senior
Work mode
Hybrid
Location
West Chester, PA, United States
Posted
Yesterday
DockerFastAPIGCPMicroservicesAWSMLOpsAzureGenerative AIGitKubernetesLLMPythonREST
Job Description
Role: Senior Agentic AI Developer
Location: Remote
Schedule: EST Hours
Rate: $85/hour W2
We are seeking a Senior Agentic AI Developer to design, build, and deploy enterprise-grade AI agents and intelligent automation solutions. This role will focus on developing agentic AI applications, Retrieval-Augmented Generation (RAG) systems, LLM-powered workflows, and scalable AI platforms using Python and modern AI frameworks.
The ideal candidate has hands-on experience building production AI systems, integrating Large Language Models (LLMs), orchestrating multi-agent workflows, and deploying cloud-native applications that support real-world business processes.
Responsibilities
Required Qualifications
Preferred Qualifications
Technical Environment
#INDCEI
#ZR
Location: Remote
Schedule: EST Hours
Rate: $85/hour W2
We are seeking a Senior Agentic AI Developer to design, build, and deploy enterprise-grade AI agents and intelligent automation solutions. This role will focus on developing agentic AI applications, Retrieval-Augmented Generation (RAG) systems, LLM-powered workflows, and scalable AI platforms using Python and modern AI frameworks.
The ideal candidate has hands-on experience building production AI systems, integrating Large Language Models (LLMs), orchestrating multi-agent workflows, and deploying cloud-native applications that support real-world business processes.
Responsibilities
- Design, develop, and deploy agentic AI applications using modern LLM frameworks and orchestration platforms.
- Build Retrieval-Augmented Generation (RAG) solutions leveraging enterprise data sources, vector databases, and semantic search technologies.
- Develop AI agents capable of tool calling, workflow automation, reasoning, and decision support.
- Create scalable APIs and backend services to support AI-enabled products and applications.
- Design and implement document ingestion, knowledge retrieval, embedding generation, and context management pipelines.
- Collaborate with product, engineering, and business teams to identify and deliver AI-driven solutions.
- Evaluate, test, and optimize LLM performance, response quality, latency, and reliability.
- Implement monitoring, observability, security, and governance controls for enterprise AI systems.
- Participate in architecture discussions, proof-of-concept development, and technical design reviews.
- Create and maintain technical documentation, implementation plans, and best practices for AI development.
Required Qualifications
- Bachelor's degree in Computer Science, Software Engineering, Data Science, or a related technical field.
- 5+ years of software development experience with strong proficiency in Python.
- Experience building and deploying Generative AI, LLM, or Agentic AI solutions in production environments.
- Experience developing RAG architectures and integrating vector databases.
- Strong understanding of prompt engineering, embeddings, semantic search, and LLM evaluation techniques.
- Experience building APIs and microservices using Python frameworks such as FastAPI.
- Experience with cloud platforms such as AWS, Azure, or GCP.
- Experience with containerization and deployment technologies including Docker and Kubernetes.
- Strong troubleshooting, debugging, and problem-solving skills.
Preferred Qualifications
- Experience with LangChain, LangGraph, CrewAI, AutoGen, or similar agent orchestration frameworks.
- Experience integrating AI agents with enterprise systems, databases, APIs, and workflow platforms.
- Familiarity with OpenAI, Anthropic, Azure OpenAI, Amazon Bedrock, or other enterprise LLM platforms.
- Experience with MLOps, LLMOps, and AI governance practices.
- Experience developing multi-agent systems and autonomous workflow solutions.
- Exposure to Go or other backend programming languages.
Technical Environment
- Python
- FastAPI
- LangChain / LangGraph
- OpenAI, Claude, Azure OpenAI, Amazon Bedrock
- Retrieval-Augmented Generation (RAG)
- Vector Databases
- Docker & Kubernetes
- AWS / Azure / GCP
- REST APIs & Microservices
- Git, CI/CD Pipelines
- LLMOps & Monitoring Frameworks
#INDCEI
#ZR
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