Very Urgent || AI/ML Architect – Agentic AI & Generative AI || Fort Mill, SC (Hybrid – 3 Days Onsite)

[Saim Ansari]

Hi, 

Hope you are doing great!   

We are having an urgent C2C requirement open for "  Architect – Agentic AI & Generative AI  "  with one of our client at  Fort Mill, SC (Hybrid – 3 Days Onsite)

AI/ML Architect – Agentic AI & Generative AI
Location: Fort Mill, SC (Hybrid – 3 Days Onsite)
Employment Type: c2c

Position Overview

We are seeking a highly skilled AI/ML Architect with strong experience designing, building, and deploying Generative AI and Agentic AI solutions in production environments. The ideal candidate will have hands-on expertise in Large Language Models (LLMs), autonomous AI agents, RAG architectures, AI orchestration frameworks, cloud-native AI platforms, and enterprise-scale AI deployments.

This role requires a blend of architecture leadership and hands-on implementation, working closely with business stakeholders, engineering teams, data scientists, and cloud architects to deliver scalable AI-powered solutions.

Key Responsibilities

AI & Agentic AI Architecture

Design and implement enterprise-grade Generative AI and Agentic AI solutions for real-world business use cases.
Architect autonomous and multi-agent systems capable of reasoning, planning, task execution, and workflow orchestration.
Develop production-ready AI systems leveraging LLMs, vector databases, knowledge graphs, and retrieval frameworks.
Define AI architecture standards, governance, security, and scalability best practices.
Evaluate emerging AI technologies and recommend architecture improvements.
Generative AI & LLM Solutions

Design and deploy solutions using OpenAI, Azure OpenAI, Anthropic Claude, Gemini, Llama, Mistral, and other foundation models.
Build advanced Retrieval-Augmented Generation (RAG) architectures for enterprise knowledge management.
Optimize prompt engineering, model selection, inference strategies, and response quality.
Develop AI copilots, intelligent assistants, search solutions, and conversational AI platforms.
Implement guardrails, observability, evaluation frameworks, and responsible AI practices.
Agentic AI & Workflow Automation

Build autonomous AI agents capable of:
Planning
Decision making
Multi-step reasoning
Tool usage
Workflow execution
Develop agent orchestration frameworks using:
LangGraph
CrewAI
AutoGen
Semantic Kernel
LangChain Agents
Design human-in-the-loop and approval workflows for enterprise AI applications.
Integrate AI agents with enterprise systems, APIs, databases, and business applications.
Machine Learning & Data Engineering

Design scalable ML pipelines and model deployment frameworks.
Collaborate with data engineering teams on feature engineering, model training, and AI infrastructure.
Build AI solutions using structured and unstructured enterprise data.
Work with vector databases and embedding models for semantic search applications.
Cloud & Production Deployment

Deploy AI applications on AWS, Azure, or GCP environments.
Design scalable AI infrastructure using Kubernetes, Docker, and cloud-native services.
Implement CI/CD pipelines for AI and ML workloads.
Monitor production AI systems for performance, reliability, security, and cost optimization.
Required Qualifications

Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or related field.
15+ years of software engineering, machine learning, or AI experience.
4+ years of hands-on experience building Generative AI applications in production.
Proven experience implementing Agentic AI use cases in production environments.
Strong understanding of:
LLMs
Prompt Engineering
RAG
Fine-tuning
Embeddings
Vector Search
AI Agents
Experience with:
LangChain
LangGraph
CrewAI
AutoGen
Semantic Kernel
Strong Python programming skills.
Experience with REST APIs, microservices, and distributed systems.
Experience with Kubernetes, Docker, and cloud platforms.
Required Technical Skills

AI / ML

Generative AI
Agentic AI
LLMs
RAG
Prompt Engineering
Fine-Tuning
Embeddings
Semantic Search
AI Evaluation Frameworks
Frameworks & Tools

LangChain
LangGraph
CrewAI
AutoGen
Semantic Kernel
Hugging Face
OpenAI APIs
Azure OpenAI
Programming

Python
SQL
REST APIs
FastAPI
Cloud & DevOps

AWS / Azure / GCP
Kubernetes
Docker
Terraform
CI/CD Pipelines
Vector Databases

Pinecone
Weaviate
ChromaDB
FAISS
Azure AI Search
Preferred Qualifications

Experience building enterprise AI copilots and AI assistants.
Experience with multi-agent orchestration frameworks.
Knowledge of MLOps and LLMOps best practices.
Experience implementing AI governance, security, and compliance frameworks.
Experience within Banking, Financial Services, Healthcare, or Insurance domains.
Experience with Knowledge Graphs and GraphRAG.
Exposure to AI observability tools such as LangSmith, Arize, Phoenix, or Weights & Biases.
Interview Focus Areas

Candidates should be able to demonstrate:

Production Agentic AI implementations.
Real-world Generative AI deployments.
RAG architecture design.
Multi-agent orchestration frameworks.
LLM evaluation and observability.
Cloud deployment and scaling strategies.
End-to-end AI solution architecture and leadership.
Must Have

✅ Agentic AI Production Experience
✅ Generative AI Production Experience
✅ RAG Architecture
✅ Python
✅ Cloud (AWS/Azure/GCP)
✅ LLM Frameworks (LangChain/LangGraph/CrewAI)
✅ AI Solution Architecture