AI/ML & MLOps Engineer

Harvey Nash; Houston (TX); On-site; USD 120,000 - 180,000; Full time

Job summary

Harvey Nash Houston is seeking an AI/ML & MLOps Engineer to design, implement, and operate scalable ML systems across cloud-native services, REST APIs, and microservices. The role emphasizes hands-on Python development, containerization, CI/CD workflows, and robust model deployment.

You will prototype quickly with AI tools, evaluate outputs, monitor models in production, and collaborate with teams to meet regulatory and security expectations in fintech-informed contexts.

Qualifications

• 3+ years in software/ML/DevOps or data engineering.
• Strong Python, Docker, Git, CI/CD, and REST API/microservices.
• Hands-on cloud infrastructure and model deployment/monitoring.
• Experience with GenAI, RAG, prompts, vector databases, and LangChain/LlamaIndex/MLflow.

Skills

Python

Docker

Git

CI/CD

REST APIs

AI prototyping

Education

Bachelor's degree in CS/Data Science or equivalent

Tools

LangChain

LlamaIndex

MLflow

Kubernetes

Job description

Job Title: AI/ML & MLOps Engineer

Location: Houston TX 77056

Duration: Full time

Required Qualifications

3+ years in software engineering, ML engineering, DevOps, or data engineering.

Core Tech: Strong Python, Docker, Git, CI/CD, and REST API/microservices architecture.

Cloud & MLOps: Hands-on experience with cloud infrastructure (AWS, Azure, or GCP) and model deployment/monitoring tools.

AI & LLM Stack: Hands-on experience with GenAI, RAG architectures, prompt engineering, vector databases, and frameworks (e.g., LangChain, LlamaIndex, MLflow).

Mindset: Strong ability to rapidly prototype with AI tools, review AI-generated code critically, and solve problems resourcefully.

Nice to Have

• Experience in fintech, banking, credit unions, or regulated industries (familiarity with core platforms like Fiserv, Jack Henry, or Corelation).
• Experience with enterprise AI governance, model-risk management, and secure agent development.
• Degree in Computer Science, Data Science, or equivalent practical experience.