Senior GenAI Python Engineer

Job Description: Senior GenAI Python Engineer

Location: Charlotte, NC - Hybrid

Employment Type: 6-12 Months Contract

Duration: 6-12 Months

Job Details:

Must Have Skills

GEN AI, Agentic AI, Python, RAG, LLM, LangChain, LangGraph, MCP, FastAPI, Microservices, CI/CD, Cloud (AWS, Google Cloud Platform), ETL, Distributed Systems, React JS, Django, Flask

Nice to have skills

Prompt Engineering, React.js, Kafka, Docker, Kubernetes, Terraform, Jenkins, GitHub 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 LangChain, LangGraph, MCP, and RAG pipelines. Strong experience in API development, microservices architecture, ETL pipelines, and cloud-native solutions across AWS and Google Cloud Platform 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, LangChain, and LangGraph 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, GitHub Actions, Docker, and cloud services.

•       Work with databases and data pipelines to process large-scale structured and unstructured datasets

Required Skills & 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 LangChain and vector databases.
• Experience building agentic AI workflows using LangGraph 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 Google Cloud Platform 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.

Top 3 responsibilities you would expect the Subcon to shoulder and execute

• Strong experience in developing AI-powered applications, RAG pipelines, and agentic AI frameworks using Python, LangChain, LangGraph, and MCP.
• Strong experience in building scalable APIs, microservices, and cloud-native deployments with CI/CD automation.
• Strong experience in data processing, ETL pipelines, and integrating enterprise systems with AI solutions.