Agentic AI Lead

Cortex Consultants LLC; Dallas (TX); On-site; USD 150,000 - 210,000; Part time

Job summary

Cortex Consultants LLC is seeking an Agentic AI Lead to design, build, and deploy autonomous AI systems. You will move beyond prompt engineering to create self-reasoning agents that execute complex workflows, integrating them into a Microservices Architecture and leveraging MCP to connect LLMs with enterprise data sources and secure APIs.

You will architect multi-agent systems, develop MCP tooling, and wrap AI agents into scalable microservices using Docker and Kubernetes, ensuring token

Qualifications

• Proficient in Python or TypeScript and related AI tooling.
• Experience building autonomous AI agents and multi-agent systems.
• Strong understanding of MCP and enterprise data integration.
• Deep knowledge of distributed systems, APIs, and microservices.
• Hands-on with Docker, cloud platforms, and scalable deployments.
• Experience with vector databases, semantic search, and RAG pipelines.

Responsibilities

• Translate client problems into technical product specs for engineering teams.
• Communicate limitations and propose viable alternative architectures.
• Design and deploy multi-agent architectures with autonomous planning and execution.
• Develop MCP servers/clients to securely expose data to LLMs.
• Wrap AI agents, RAG engines, and vector stores into scalable microservices.
• Optimize agentic workflows for efficiency and accuracy.

Skills

Python/TypeScript

LangGraph/CrewAI/AutoGen/LangChain

MCP protocol

Distributed systems

Docker & Cloud

Vector databases & RAG

Tools

Docker

Kubernetes

Kafka/RabbitMQ

REST/gRPC APIs

Job description

Title: Agentic AI Lead

Location: Dallas, TX / San Jose, CA

Employment Type: Contract to hire

Experience: 10 years to 15 years

Role Overview

We are seeking an Agentic AI Lead to design, build, and deploy autonomous AI systems. In this role, you will move beyond basic prompt engineering to create self-reasoning agents that execute complex workflows. You will integrate these agents into our Microservices Architecture and leverage the Model Context Protocol (MCP) to connect LLMs seamlessly with enterprise data sources, development environments, and secure APIs.

Key Responsibilities

• Translate Needs: Convert ambiguous client business problems into highly technical product specifications for engineering activities.
• Manage Expectations: Communicate limitations transparently while proposing viable alternative architectures
• Agent Architecture: Design and deploy multi-agent systems capable of autonomous planning, reasoning, reflection, and task execution
• MCP Tooling Development: Build and maintain Model Context Protocol (MCP) servers and clients to securely expose data, file systems, and enterprise tools to LLMs.
• Microservices Integration: Wrap AI agents, RAG engines, and vector stores into modular, scalable microservices using Docker and Kubernetes.
• Tool & API Orchestration: Implement advanced tool-calling architectures to connect LLMs to production databases, external APIs, and internal software systems
• Pipeline Optimization: Evaluate and optimize agentic workflows for token efficiency, latency, context-window usage, and decision-making accuracy.

Required Skills & Qualifications

• Programming: Expert proficiency in Python or TypeScript.
• AI Orchestration: Hands-on experience with LangGraph, CrewAI, AutoGen, or LangChain.
• Model Context Protocol: Practical experience implementing or consuming open-source and custom MCP tools/servers.
• Architecture: Deep understanding of distributed systems, REST/gRPC APIs, message brokers (Kafka/RabbitMQ), and microservice communication.
• Cloud & DevOps: Strong experience with containerization (Docker) and deploying services to cloud infrastructure (AWS, GCP, or Azure).
• AI Expertise: Experience on vector databases embeddings, semantic search, and RAG pipelines