GEN AI engineer & Agentic AI Engineer
Listed on 2026-07-01
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Software Development
AI Engineer (Applied/Software), Cloud Engineer - Software, Backend Developer, DevOps
GEN AI Engineer & Agentic AI Engineer
Work Location:
Charlotte, NC or hybrid work set-up at NC office
Contract duration: 6-12 months depending performance
Interview Process (Is face to face required?):
Yes (Either in Dallas, TX or in Charlotte, NC at Client office)
Must Have
Skills:
GEN AI, Agentic AI, Python, RAG, LLM, Lang Chain, Lang Graph, MCP, FastAPI, Microservices, CI/CD, Cloud (AWS, GCP), ETL, Distributed Systems, React JS, Django, Flask
Nice to have skills:
Prompt Engineering, React.js, Kafka, Docker, Kubernetes, Terraform, Jenkins, Git Hub Actions, Databases (PostgreSQL, MongoDB, Oracle, Snowflake)
We are seeking a highly skilled Python Developer with experience in building scalable enterprise applications and AI-powered platforms. The candidate has hands-on experience in Generative AI, LLM-driven applications, and agentic AI solutions using frameworks like Lang Chain, Lang Graph, MCP, and RAG pipelines. Strong experience in API development, microservices architecture, ETL pipelines, and cloud-native solutions across AWS and GCP environments.
Key Responsibilities:- Design and implement Generative AI models for text, image, or multimodal applications.
- Design and develop scalable full-stack enterprise applications using Python, FastAPI, and React.js.
- Build and optimize RESTful and asynchronous APIs for secure enterprise integrations and AI-driven applications.
- Develop and implement AI agent frameworks using MCP, Lang Chain, and Lang Graph for enterprise use cases.
- Design and implement Retrieval-Augmented Generation (RAG) pipelines for intelligent search and contextual query processing.
- Develop microservices and distributed systems for AI agent lifecycle management and real-time data processing.
- Implement CI/CD pipelines and automate deployments using Jenkins, Git Hub Actions, Docker, and cloud services.
- Work with databases and data pipelines to process large-scale structured and unstructured datasets
Qualifications:
- 4+ years of experience in Python development, AI applications, and enterprise systems.
- Hands-on experience with Generative AI, LLMs, and RAG-based solutions using Lang Chain and vector databases.
- Experience building agentic AI workflows using Lang Graph and MCP frameworks.
- Strong experience in API and microservices development using FastAPI, Django, and Flask.
- Experience in CI/CD automation and containerized deployments using Docker and Kubernetes.
- Experience working on cloud platforms such as AWS and GCP with cloud-native architectures.
- Strong knowledge of databases including PostgreSQL, MongoDB, Oracle, Snowflake, and Teradata.
- Experience with ETL pipelines, distributed data processing, and tools like PySpark, Pandas, and AWS Glue.
- Experience with Kafka event streams and real-time data pipelines.
- Strong proficiency in Agile SDLC, performance optimization, and scalable system design.
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