AI Engineer III

Vaco; San Antonio (TX); On-site; USD 110,000 - 170,000; Full time

Job summary

Vaco is seeking an AI Engineer III to design, build, and deploy next‑gen Agentic AI applications. You will work across AI architecture, cloud infrastructure, and production support, building scalable, secure AI services while mentoring peers.

You will contribute across the full stack from development to production, integrating LLMs, RAG, embeddings, and tools into enterprise workflows. This role emphasizes hands‑on engineering and cross‑team collaboration in a fast‑paced environment.

Qualifications

• Strong full-stack software development background.
• Broad software engineering and IT experience beyond AI.
• Hands-on Agentic AI development experience.
• Deep understanding of AI agents, orchestration, tool use, and multi-agent workflows.
• Experience with LangGraph, LangChain, or similar agentic frameworks.
• Strong experience integrating LLMs into production applications.
• Experience with RAG, embeddings, and vector databases.

Responsibilities

• Design, develop, and deploy production-grade Agentic AI applications.
• Build agent-based and multi-agent workflows that interact with enterprise applications and data.
• Develop AI solutions using LLMs, RAG, embeddings, vector databases, and modern AI frameworks.
• Build and integrate APIs, services, tools, and enterprise applications.
• Take applications from development and UAT through production deployment.
• Work across the full software development lifecycle.
• Support cloud infrastructure, servers, networking, and application environments as needed.
• Build scalable, secure, and reliable AI services.
• Work with DevOps and CI/CD processes to automate application deployment.
• Troubleshoot complex application and infrastructure issues.
• Participate in technical architecture and engineering decisions.
• Support security, governance, and audit requirements.
• Mentor other engineers and provide technical direction while remaining hands-on.
• Help establish engineering standards and best practices as the AI environment grows.

Skills

Full-stack software development

Agentic AI development

AI agents orchestration

LangGraph LangChain experience

Production integration of LLMs

RAG embeddings vector databases

APIs integration

Python Java C# JavaScript

AWS Azure cloud

Containers microservices CI/CD

DevOps practices

Production deployment lifecycle

Job description

AI Engineer III

Position Overview

We’re looking for a highly technical, hands‑on AI Engineer to help design, build, and deploy the next generation of AI-powered applications.

This is not a role for someone whose AI experience stops at basic LLM integrations or RAG implementations. We’re looking for a strong software engineer first who has evolved into AI engineering and has real experience developing Agentic AI solutions.

The environment is highly hands‑on. You’ll have the opportunity to work across application development, AI architecture, cloud infrastructure, deployment, networking, and production support. The team is actively building several new AI solutions with additional development planned over the next 12 months.

What You’ll Be Doing

• Design, develop, and deploy production‑grade Agentic AI applications
• Build agent‑based and multi‑agent workflows that interact with enterprise applications and data
• Develop AI solutions using LLMs, RAG, embeddings, vector databases, and modern AI frameworks
• Build and integrate APIs, services, tools, and enterprise applications
• Take applications from development and UAT through production deployment
• Work across the full software development lifecycle
• Support cloud infrastructure, servers, networking, and application environments as needed
• Build scalable, secure, and reliable AI services
• Work with DevOps and CI/CD processes to automate application deployment
• Troubleshoot complex application and infrastructure issues
• Participate in technical architecture and engineering decisions
• Support security, governance, and audit requirements
• Mentor other engineers and provide technical direction while remaining hands‑on
• Help establish engineering standards and best practices as the AI environment continues to grow

Must-Have Experience

• Strong full‑stack software development background
• Broad software engineering and IT experience beyond AI alone
• Hands‑on Agentic AI development experience
• Deep understanding of AI agents, orchestration, tool use, and multi‑agent workflows
• Experience with LangGraph, LangChain, or similar agentic frameworks
• Strong experience integrating LLMs into production applications
• Experience with RAG, embeddings, and vector databases
• Experience developing APIs and integrating multiple systems
• Strong programming background with languages such as Python, Java, C#, and/or JavaScript
• Experience with cloud environments such as AWS or Azure
• Understanding of containers, microservices, CI/CD, and modern DevOps practices
• Ability to take an application from development through production
• Comfortable working across multiple areas of the technology stack rather than operating within a narrow specialty

What Will Separate the Best Candidates

The strongest candidates will be able to clearly explain:

• What they built before moving into AI
• Production applications they personally designed and developed
• Agentic AI systems they have built hands‑on
• How their agents reason, use tools, interact with data, and communicate with other systems
• How they moved AI applications from development into production
• Technical challenges they personally solved rather than projects where they were simply part of the team

RAG experience by itself is not enough for this position. We’re specifically looking for engineers with deeper Agentic AI development experience.