Job Title: AI Engineer (LLMs | MCP | RAG | Agentic AI)
Client: HCSC (Healthcare)
Location: Remote
Job Type: Contract
Experience: 5+ Years
Job Summary
We are seeking experienced AI Engineers with strong expertise in Large Language Models (LLMs), Model Context Protocol (MCP), Retrieval-Augmented Generation (RAG), Python, Prompt Engineering, and Agentic AI. The ideal candidate will design and develop enterprise-grade AI applications, integrate LLMs with enterprise systems, build intelligent AI agents, and deliver scalable AI solutions using leading cloud AI platforms. Experience in Healthcare, Contact Center AI, and multi-agent architectures is highly preferred.
Must-Have Skills
- Large Language Models (LLMs)
- Model Context Protocol (MCP)
- Retrieval-Augmented Generation (RAG)
- Python
- Prompt Engineering
- Agentic AI Development
Preferred Skills
- Contact Center AI Solutions
- Azure OpenAI
- AWS Bedrock
- Google Vertex AI
- AI Application Architecture
- REST API Integration
Nice-to-Have Skills
- Healthcare Domain Experience
- Multi-Agent Frameworks
- Vector Databases (Pinecone, ChromaDB, FAISS, Weaviate)
- Conversational AI Platforms
Key Responsibilities
- Design, develop, and deploy enterprise AI applications using Large Language Models (LLMs).
- Build intelligent AI agents using Model Context Protocol (MCP), Agentic AI frameworks, and multi-agent orchestration.
- Develop Retrieval-Augmented Generation (RAG) pipelines using vector databases and enterprise knowledge sources.
- Engineer high-quality prompts and optimize AI workflows for accuracy, performance, latency, and cost.
- Develop scalable Python applications for AI services, APIs, automation, and integrations.
- Integrate AI solutions with enterprise applications, Contact Center platforms, and cloud services.
- Build and optimize AI applications using Azure OpenAI, AWS Bedrock, or Google Vertex AI.
- Design and implement REST APIs for AI-powered services and enterprise integrations.
- Collaborate with business stakeholders, architects, and engineering teams to translate business requirements into AI solutions.
- Perform AI model evaluation, testing, monitoring, debugging, and continuous optimization.
- Follow best practices for Responsible AI, AI governance, security, and enterprise deployment.
Required Qualifications
- 5+ years of software engineering experience with strong expertise in AI application development.
- Hands-on experience with Large Language Models (LLMs).
- Experience implementing Model Context Protocol (MCP) for AI agent integration.
- Strong expertise in Retrieval-Augmented Generation (RAG) architectures.
- Advanced Python programming skills.
- Experience with Prompt Engineering and LLM optimization.
- Experience building Agentic AI applications and autonomous workflows.
- Strong understanding of REST APIs and enterprise application integration.
Excellent analytical, problem-solving, and communication skills.