Senior AI Agent Engineer - Production AI & Cloud

Jobtailor

Houston (TX)

On-site

USD 120,000 - 180,000

Full time

45 hours ago

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Job summary

Jobtailor in Houston, TX seeks an AI/ML engineer to design, develop, and deploy enterprise-grade AI agents enhancing supply chain operations. You will implement MCP/A2A protocols, leverage MCP frameworks, and collaborate with data engineers to build robust data pipelines.

You will work with Python, SQL, Flask and FastAPI, containerize with Docker, and orchestrate via Kubernetes while aligning with security and DevOps practices. Leadership expects proactive roadmap contributions.

Qualifications

Bachelor's degree in Computer Science, Artificial Intelligence, Data Science, Information Technology, Engineering, or a related field, or equivalent experience.
3 to 5 years of experience in software engineering, AI/ML engineering, or data science
At least 1 year focused on agentic AI development
Hands-on experience with AI agent development frameworks such as Google's Agent Development Kit or OpenAI Agents SDK
Knowledge of Model Context Protocol (MCP) and Agent-to-Agent (A2A) communication protocols
Strong proficiency with cloud environments, preferably Google Cloud Platform (GCP); experience with AWS or Azure also considered
Advanced experience with Python, APIs, SQL, system design, DevOps/AIOps practices
Familiarity with JavaScript and modern frontend technologies
Experience monitoring, troubleshooting, and optimizing production AI and software solutions
Strong analytical, problem-solving, and decision-making skills
Ability to manage multiple priorities and thrive in a fast‑paced, innovative environment
Experience with advanced AI techniques, including fine‑tuning large language models and developing custom AI algorithms
Familiarity with logistics, supply chain, warehouse management, or transportation management systems
Experience with Snowflake and related data platforms
Hands‑on experience with GCP Vertex AI Agent Builder
Experience deploying enterprise‑scale AI solutions in production environments
Background supporting AI governance, model evaluation, and responsible AI initiatives
All applicants who receive a conditional offer of employment may be required to take and pass a pre‑employment drug test

Responsibilities

Design, develop, deploy, and maintain AI agents and software solutions that enhance supply chain operations and technology.
Apply prompt engineering, Retrieval-Augmented Generation (RAG), LLM orchestration frameworks, MCP/function calling, evaluation techniques, and guardrails to optimize LLM integrations and build enterprise AI agents.
Incorporate software engineering, DevOps, and cybersecurity best practices, including CI/CD pipelines, source control, and secure coding standards.
Design and develop, or collaborate with data engineering teams to build data models and pipelines supporting AI solutions.
Develop AI agent software and system integrations using Python, SQL, Flask, and FastAPI.
Build scalable and portable AI solutions using Docker and Kubernetes.
Partner with business and product stakeholders to understand requirements, identify opportunities, and educate teams on AI capabilities and best practices.
Collaborate with infrastructure, Information Security, and data engineering teams to define requirements and integrate AI solutions.
Communicate project status, risks, and opportunities with leadership and key stakeholders.
Own projects from concept through production deployment with minimal supervision.
Mentor junior engineers through code reviews, pair programming, technical coaching, and architectural guidance.
Stay current on emerging AI technologies and contribute to the organization’s AI strategy and roadmap.