C2C Job OpportunityAgentic AI Lead -Dallas, TX / San Jose, CA

15 Years (USC/GC)

 

Title: Agentic AI Lead

Location: Dallas, TX / San Jose, CA

Job Type: Contract to hire after 6 months

 

Role Overview

We are seeking an Agentic AI Developer 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