Generative AI Engineer

Ampcus Inc; Chantilly (VA); On-site; USD 120,000 - 170,000; Full time

Job summary

Ampcus Inc is seeking a highly skilled MCP, RAG, and Connectors Engineer to design, build, and optimize AI-powered solutions interfacing enterprise data with LLMs in Chantilly, VA. You will craft MCP servers, RAG pipelines, and custom connectors for secure, scalable AI experiences.

You will collaborate with Data Scientists, AI Engineers, and Product teams to deliver reusable integration frameworks, observability, and governance, while advancing deployment through CI/CD for AI services.

Qualifications

• Strong understanding of Large Language Models (GPT, Claude, Gemini, Llama, etc.).
• Hands-on experience with LangChain, Semantic Kernel, AI Agents and Tool Calling.
• Experience with MCP architecture, server development, and tool registration.
• Familiarity with REST/GraphQL APIs, OAuth 2.0/OpenID Connect, Microsoft Graph API.

Responsibilities

• Design and develop MCP servers and tools for LLM-driven applications.
• Implement tool-calling frameworks and agent integrations.
• Enable secure exposure of enterprise capabilities to AI assistants.
• Manage authentication, authorization, and governance of MCP services.
• Optimize context-sharing mechanisms between AI models and enterprise systems.
• Design and implement enterprise-grade RAG architectures.
• Build document ingestion, chunking, embedding, indexing, and retrieval pipelines.
• Integrate vector databases and semantic search solutions.
• Improve answer quality through reranking, hybrid search, and prompt optimization.
• Monitor retrieval accuracy, latency, and hallucination rates.
• Evaluate and implement advanced retrieval techniques.

Skills

Python

FastAPI

Flask

Node.js

SDK development

API development

Tools

LangChain

Semantic Kernel

Pinecone

Weaviate

Chroma

Elasticsearch/OpenSearch

Docker

Kubernetes

AWS

Google Cloud

Job description

We are seeking a highly skilled MCP (Model Context Protocol), RAG (Retrieval-Augmented Generation), and Connectors Engineer to design, build, and optimize AI-powered solutions that integrate enterprise data sources with Large Language Models (LLMs). The ideal candidate will have hands-on experience with AI platforms, enterprise integrations, vector databases, retrieval pipelines, APIs, and modern AI application architectures.

The role will focus on enabling secure, scalable, and context-aware AI experiences by developing MCP servers, building RAG pipelines, and integrating enterprise systems through custom connectors.

Key Responsibilities

• Design and develop MCP servers and tools for LLM-driven applications.
• Implement tool-calling frameworks and agent integrations.
• Enable secure exposure of enterprise capabilities to AI assistants.
• Manage authentication, authorization, and governance of MCP services.
• Optimize context-sharing mechanisms between AI models and enterprise systems.
• Design and implement enterprise-grade RAG architectures.
• Build document ingestion, chunking, embedding, indexing, and retrieval pipelines.
• Integrate vector databases and semantic search solutions.
• Improve answer quality through reranking, hybrid search, and prompt optimization.
• Monitor retrieval accuracy, latency, and hallucination rates.
• Evaluate and implement advanced retrieval techniques.

Connectors & Integrations

• Develop connectors for enterprise systems such as:
• SharePoint
• Microsoft Graph
• ServiceNow
• SAP
• Databases (SQL/NoSQL)
• Internal APIs
• Build API integration frameworks and data synchronization pipelines.
• Implement event-driven and real-time data access patterns.
• Ensure scalability, security, and data compliance requirements.

AI Platform Development

• Collaborate with Data Scientists, AI Engineers, and Product Teams.
• Build reusable AI integration frameworks and SDKs.
• Develop observability, monitoring, and governance solutions.
• Implement CI/CD pipelines for AI services.
• Support production deployment and operational excellence.

Required Skills

AI & LLM Technologies

• Strong understanding of Large Language Models (GPT, Claude, Gemini, Llama, etc.)
• Hands-on experience with:
• LangChain
• Semantic Kernel
• AI Agents and Tool Calling

RAG Expertise

• Embeddings and vector search
• Semantic search and hybrid retrieval
• Evaluation frameworks for RAG systems

MCP Knowledge

• Understanding of MCP architecture and ecosystem
• MCP server development and tool registration
• Context management and agent integration

Integration Development

• REST APIs
• GraphQL APIs
• OAuth 2.0 / OpenID Connect
• Microsoft Graph API

Programming Skills

• Python (mandatory)
• FastAPI, Flask, Node.js
• SDK and API development

Data & Search Technologies

• Pinecone
• Weaviate
• Chroma
• Elasticsearch / OpenSearch
• SQL and NoSQL databases
• AWS or Google Cloud (good to have)
• Docker and Kubernetes

Preferred Qualifications

• Experience building Microsoft Copilot extensions and plugins.
• Experience with Copilot Studio and Microsoft Graph Connectors.
• Understanding of enterprise security and governance frameworks.
• Exposure to Agentic AI and multi-agent architectures.
• Knowledge of MLOps and AI observability tools.

Success Metrics

• Improved retrieval accuracy and response quality.
• Reduced AI hallucinations through optimized RAG pipelines.
• Successful integration of enterprise data sources.
• High availability and performance of MCP services.
• Adoption of AI solutions across business functions.