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Agentic AI Developer, Plano, TX (Hybrid)

MetaRPOPlano, TX🇺🇸United StatesPosted Oct 6, 2026

Quick Overview

Seniority
Mid Senior
Work mode
Hybrid
Location
Plano, TX, United States
Posted
2 days ago
DockerMicroservicesSQLAWSAgileAzureGPTGenerative AIGitGoogle CloudKafkaKubernetesLLMPythonREST

Job Description

Agentic AI Developer
Locations: Plano, TX / Columbus, OH
Job Type: Contract / Long-Term
Work Arrangement: Hybrid
Duration: Long-Term

Job Summary

Seeking an experienced Agentic AI Developer to design, develop, and deploy intelligent AI agents and enterprise-grade generative AI solutions. The ideal candidate will have strong hands-on experience with Python, LLMs, AI agents, RAG, prompt engineering, tool/function calling, and cloud-based AI platforms.

The candidate will work with engineering, data science, product, and architecture teams to build secure, scalable, and production-ready AI solutions for enterprise and financial-services use cases.

Key Responsibilities

  • Design, develop, and deploy agentic AI applications using LLMs and modern AI frameworks.
  • Build autonomous and semi-autonomous AI agents capable of reasoning, planning, decision-making, and executing tasks through tools and APIs.
  • Develop multi-agent workflows and orchestration patterns for complex enterprise use cases.
  • Implement Retrieval-Augmented Generation (RAG) solutions using enterprise data sources.
  • Integrate LLMs with internal systems, APIs, databases, and enterprise applications.
  • Develop tool/function calling capabilities that allow AI agents to interact with business systems.
  • Work with frameworks such as LangChain, LangGraph, Semantic Kernel, AutoGen, CrewAI, or similar agentic AI frameworks.
  • Develop prompt templates, system instructions, evaluation strategies, and guardrails for LLM applications.
  • Implement vector search and embedding-based solutions using technologies such as Pinecone, OpenSearch, Azure AI Search, or similar platforms.
  • Develop AI applications using Python and REST APIs.
  • Integrate AI solutions with cloud platforms and enterprise infrastructure.
  • Implement security, governance, observability, and responsible-AI practices for production AI applications.
  • Monitor AI agent performance, latency, accuracy, reliability, and cost.
  • Build automated testing and evaluation frameworks for LLM and agentic applications.
  • Collaborate with architects, data engineers, product managers, and business stakeholders.
  • Participate in code reviews, technical design sessions, and Agile development activities.

Required Skills

  • Hands-on experience building Generative AI / LLM applications.
  • Strong understanding of Agentic AI concepts and AI agent architectures.
  • Experience with LLMs such as GPT, Claude, Gemini, Llama, or similar models.
  • Strong experience with Python and API development.
  • Experience with LangChain, LangGraph, Semantic Kernel, AutoGen, CrewAI, or equivalent frameworks.
  • Strong understanding of RAG architecture.
  • Experience with embeddings, vector databases, semantic search, and document retrieval.
  • Experience implementing function/tool calling and API integrations.
  • Strong knowledge of prompt engineering and LLM orchestration.
  • Experience with REST APIs and microservices.
  • Experience with cloud platforms such as AWS, Azure, or Google Cloud Platform.
  • Experience with Git, CI/CD, testing, and production deployment.

Preferred Skills

  • Experience developing multi-agent systems.
  • Experience with Model Context Protocol (MCP) and MCP-based tool integrations.
  • Experience with Google ADK, LangGraph, or similar agent orchestration frameworks.
  • Experience with AWS services such as Bedrock, Lambda, S3, ECS/EKS, and OpenSearch.
  • Experience with Kubernetes and Docker.
  • Knowledge of AI/LLM security, governance, and responsible AI.
  • Experience with LLM observability and evaluation tools.
  • Experience with Kafka or event-driven architectures.
  • Strong SQL and database knowledge.
  • Experience in the banking/financial services domain.

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