GenAI Engineer

MACHINE LEARNING TECHNOLOGIES LLC; Plano (TX); Presencial; USD 93.000 - 133.000; Jornada completa

Descripción de la vacante

MACHINE LEARNING TECHNOLOGIES LLC is seeking a GenAI Engineer in Plano, TX to design and deliver scalable AI applications and APIs. You will work across the full lifecycle from development to deployment, monitoring, and observability.

The role emphasizes hands-on experience with FastAPI, FastMCP, and Azure, plus integrating LLMs such as OpenAI GPT and Claude, with containerized DevOps practices and modern tooling.

Formación

• Must have all five mandatory skills: FastAPI, FastMCP, Agentic Workflows, LLM/GenAI, and Microsoft Azure.
• Strong Python proficiency with API design using FastAPI and FastMCP.
• Hands-on GenAI deployment, monitoring, and observability experience.
• Experience deploying GenAI solutions in Azure and integration with LLMs.
• Familiarity with DevOps practices and containerization (Docker/Kubernetes).

Responsabilidades

• Design and develop scalable GenAI applications and production-grade APIs.
• Build agentic workflows and LLM-powered solutions.
• Integrate with OpenAI GPT and Anthropic Claude for deployments.
• Develop and deploy in Microsoft Azure environments.
• Own end-to-end lifecycle: development, deployment, monitoring, and observability.
• Implement CI/CD with Docker, Kubernetes/AKS, and GitHub Actions.

Conocimientos

FastAPI

FastMCP

Agentic Workflows

LLM/GenAI

Microsoft Azure

Herramientas

Docker

Kubernetes

GitHub Actions

Descripción del empleo

Job Overview

• Job ID: J55091


• Job Title: GenAI Engineer


• Location: Plano, TX


• Duration: 8 Months + Extension


• Domain Exposure: Healthcare


• Client: To Be Discussed Later


• Employment Type: W-2, 1099, C2C


• Work Authorization: US Citizen, Green Card, H-1B, OPT-EAD, CPT, H4-EAD, Other


• Bill Rate: $82/hour (C2C)

Job Description

We are looking for an experienced GenAI Engineer to design and develop scalable, production‑grade AI applications and APIs. The role requires strong hands‑on expertise in FastAPI, FastMCP, Agentic Workflows, LLM/GenAI, and Microsoft Azure, with responsibility across the full application lifecycle from development through deployment, monitoring, and observability.

Responsibilities

• Design and develop scalable GenAI applications and production‑grade APIs using Python, FastAPI, and FastMCP.


• Build and implement agentic workflows and LLM‑powered solutions.


• Integrate applications with LLMs such as OpenAI GPT and Anthropic Claude.


• Develop and deploy solutions within Microsoft Azure environments.


• Own end‑to‑end application development, deployment, monitoring, and observability.


• Implement containerization and CI/CD practices using Docker, Kubernetes/AKS, and GitHub Actions.


• Use AI‑assisted development tools such as Claude, Codex, and VS Code to accelerate development, debugging, and delivery.

Skills Must Have

Candidates must have ALL five mandatory skills: FastAPI, FastMCP, Agentic Workflows, LLM/GenAI, and Microsoft Azure along with strong proficiency in Python, with proven experience designing, developing, and implementing applications using FastAPI and FastMCP.

Candidates Should Have Hands‑on Experience Developing GenAI Solutions And Integrating LLMs Such As OpenAI GPT And Anthropic Claude, As Well As Experience With Deployment, Monitoring, Observability, Containerization, And Modern DevOps Practices:

Ability to build scalable, production‑grade APIs and end‑to‑end solutions, covering the complete development lifecycle from implementation and deployment to monitoring and observability.

Experience With Microsoft Azure Is Highly Preferred.

Familiarity with Azure services such as AKS, Cosmos DB, and Azure Cache for Redis is a strong plus.

Solid hands‑on experience across the Generative AI ecosystem, including developing applications that consume and integrate with LLMs such as OpenAI GPT and Anthropic Claude.

Strong hands‑on experience with AI‑assisted development tools and IDEs, such as Claude, Codex, and VS Code.

Good understanding of DevOps and containerisation practices, including experience with GitHub Actions, Docker, and Kubernetes / AKS.

Equal Opportunity Employer

We are an equal opportunity employer. All aspects of employment including the decision to hire, promote, discipline, or discharge, will be based on merit, competence, performance, and business needs. We do not discriminate on the basis of race, color, religion, marital status, age, national origin, ancestry, physical or mental disability, medical condition, pregnancy, genetic information, gender, sexual orientation, gender identity or expression, national origin, citizenship/ immigration status, veteran status, or any other status protected under federal, state, or local law.