Job Title: GEN AI Python Developer
Work Location : CharlotteNC28202 (Hybrid- 3 days)
Contract duration: 12
F2F interview : Yes
UPDATE:
This is a Developer Role.
In person Interview is mandatory
Coding test will be conducted
Need Candidate from Python Development Background.
Need Someone with Strong Python Scripting Coding Experience
Also, someone who is working on Gen AI last 4 -5 years
Client is from Banking Financial Domain
No Code assistance will be provided. Candidate has to be a self-sufficient to development the code.
MCP (Model Context Protocol) experience. How to set up MCP.
Need Resume max 15 Years of experience.
Job Details:
Must Have Skills
GEN AI, Agentic AI, VLLM, fAST API, REST API, MCD, Lang Graph, Lang Chain, Graph RAG, ML Ops,Python, ML, Data Science, RAG,LLM
Nice to have skills
Google Cloud Platform, Prompt Engineering
Detailed Job Description
We are seeking a highly skilled Generative AI Engineer with a strong Python background to design, develop, and deploy cutting-edge AI solutions. The ideal candidate will have hands-on experience with Large Language Models (LLMs), prompt engineering, and Gen AI frameworks, along with expertise in building scalable AI applications. Experience in Developing Agentic AI solutions.
Key Responsibilities:
Design and implement Generative AI models for text, image, or multimodal applications.
Develop prompt engineering strategies and embedding-based retrieval systems.
Integrate Gen AI capabilities into web applications and enterprise workflows.
Build agentic AI applications with context engineering and MCP tools. Required Skills & Qualifications:
7+ years of hands-on experience in AI, Data science, ML, GEN AI
2 years of strong hands on experience in Agentic AI, VLLM’s, GEN AI, Lang Chain, Lang Graph, RAG, LLM OPS and AI Services in Google Cloud Platform and Azure.
Strong hands on experience designing and deploying Retrieval-Augmented Generation (RAG) pipelines
Strong MLOps/LLMOps experience with CI/CD automation,
Extensive experience with LangChain, LangGraph, and agentic AI patterns including routing, memory, multi-agent orchestration, guardrails, and failure recovery.
Experience in Cloud-native engineering across AWS (SageMaker, Lambda, ECS/Fargate, S3, API Gateway, Step Functions) and Google Cloud Platform (Vertex AI) for scalable AI delivery
Experience in Developing microservices and API development using FastAPI, REST APIs, Pydantic/JSON schemas, Docker, and Kubernetes for low-latency serving.
Strong Hands-on experience with vector databases and semantic search technologies including Pinecone, FAISS, ChromaDB, and embedding lifecycle management
Strong proficiency in Python and AI/ML frameworks (PyTorch, TensorFlow).
Hands on experience using session and memory for building multi-agent systems along with using MCP tools.
Hands-on experience with LLMs, transformers, and Hugging Face ecosystem.
Knowledge and experience with vector databases and RAG technique for semantic search.
Familiarity with cloud AI services (AWS SageMaker, Azure OpenAI, Google Cloud Platform Vertex AI).
Understanding of MLOps practices for scalable AI deployment.
Strong experience in working with LLM fine-tuning with LoRA, QLoRA, PEFT,
Strong experience in Architected advanced RAG systems using Pinecone, FAISS, Weaviate, Chroma, hybrid retrieval, and custom embeddings,
Strong experience in Designing end-to-end LLMOps/MLOps pipelines using MLflow, DVC, SageMaker Pipelines, Vertex AI Pipelines, and GitHub Actions
Experience in using cloud-native AI systems on AWS (SageMaker, Lambda, EKS, EC2, Step Functions, S3, Glue) and Google Cloud Platform Vertex AI, supporting high-volume inference and secure enterprise operations
Experience in developing multi-agent orchestration workflows using LangGraph and CrewAI for tool-calling, validation agents, automated reasoning, and workflow supervision
Minimum years of experience
>10 years
Certifications Needed :No
Top 3 responsibilities you would expect the Subcon to shoulder and execute
Strong communication skills
Strong programming skills
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