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# GenAI Engineer

- **Company:** Synechron Inc
- **Location:** Charlotte, NC, United States
- **Salary:** $90,000.0 - $105,000.0
- **Contract:** Permanent contract
- **Skills:** LangGraph Framework, Application Programming Interfaces (APIs), Artificial Intelligence, Microsoft Azure, Databases, Data Mining, Memory Management, Python (Programming Language), OpenAI, Search Technologies, Software Engineering, Workflow Management Systems, Pinecone, Enterprise Software Applications, Chatbots, LangChain, Retrieval-Augmented Generation, Large Language Models, Multi-Agent Systems, Prompt Engineering, Google Vertex AI, Software Application Programming, Backend, Agentic-AI, Pgvector, AngularJS, Low Latency, Weaviate, Milvus, Invoking Functions, Google Gemini, Restful APIs, Human in the Loop, ChromaDB, Microservices
- **Published:** October 13, 2026
- **Apply:** https://www.juju.com/job/2_164137363

## About the Role

We are seeking a skilled GenAI Engineer with strong experience in Python, LangChain, and LangGraph to design, develop, and deploy intelligent AI applications and agentic workflows. The ideal candidate will have hands-on experience building production-ready solutions using large language models, retrieval-augmented generation, tool-calling, and multi-agent systems., * Strong professional experience developing applications using Python.

 * Hands-on experience with LangChain and LangGraph.
 * Solid understanding of:Large language models and transformer-based architectures
 * Prompt engineering
 * Embeddings and vector search
 * Retrieval-augmented generation
 * AI agents and workflow orchestration
 * Function calling and structured data extraction
 * Experience working with LLM providers such as OpenAI, Anthropic, Google Vertex AI/Gemini, or Azure OpenAI.
 * Experience with REST APIs, microservices, and backend application development.
 * Familiarity with vector databases such as Pinecone, Weaviate, Milvus, Chroma, or pgvector.
 * Experience with Angular.

## Description

* Design, develop, and deploy generative AI applications using large language models.
 * Build LLM-powered workflows, assistants, chatbots, and automation solutions using LangChain and LangGraph.
 * Develop agentic systems with capabilities such as:Tool and function calling
 * Planning and reasoning
 * Memory management
 * Workflow orchestration
 * Human-in-the-loop approvals
 * Multi-agent collaboration
 * Implement retrieval-augmented generation (RAG) pipelines using document processing, embeddings, vector databases, and semantic search.
 * Integrate LLM applications with APIs, enterprise systems, databases, and third-party services.
 * Develop robust prompts, structured outputs, evaluation frameworks, and guardrails.
 * Optimize applications for accuracy, latency, scalability, cost, and reliability.
 * Build and maintain reusable Python services, libraries, and APIs.
 * Conduct testing and evaluation of LLM outputs, including relevance, factuality, safety, and consistency.
 * Monitor production AI systems and troubleshoot performance or quality issues.