LLMOps Engineer for Corp to corp

Overview

On Site
Depends on Experience
Part Time
Accepts corp to corp applications

Skills

LLM and Python

Job Details

Hi

I hope you are doing well.

I wanted to connect with you regarding an exciting opportunity for the position of LLMOps Engineer at Tampa FL (Onsite ). Please find below the job description for your review. If this aligns with your career aspirations, kindly share your updated resume and your best time for a quick discussion.

Job Title: LLMOps Engineer

Location: Tampa, FL(Onsite)

Rate : $50/hr. On C2C

Job Description

Verizon is seeking a highly skilled LLMOps Engineer to join our AI/ML engineering team. In this role, you will be responsible for designing, deploying, and maintaining Large Language Model (LLM) solutions in production. You will collaborate with data scientists, ML engineers, and cloud architects to ensure scalable, secure, and efficient operations of generative AI applications.

Key Responsibilities

Build and maintain end-to-end LLM pipelines, from experimentation to production.

Optimize fine-tuning, prompt engineering, and deployment of LLMs on cloud and on-prem environments.

Automate workflows for model training, versioning, monitoring, and retraining using MLOps/LLMOps best practices.

Implement observability, monitoring, and logging systems for LLMs to track performance, drift, and usage.

Work with APIs (OpenAI, Anthropic, Hugging Face, etc.) and integrate LLMs into enterprise applications.

Ensure data security, compliance, and governance for sensitive enterprise and customer data.

Collaborate with cross-functional teams to define scalable LLM architectures and improve inference efficiency.

Research and evaluate the latest LLMOps tools and frameworks (LangChain, LlamaIndex, Weaviate, Pinecone, Ray, etc.).

Required Qualifications

Bachelor s/Master s degree in Computer Science, Data Science, AI/ML, or related field.

Total 8+ Years of IT and 5+ years of experience in MLOps/DevOps/ML Engineering, with at least 2 years in LLMOps.

Strong expertise in Python, ML frameworks (TensorFlow, PyTorch, Hugging Face).

Experience with LLM frameworks: LangChain, LlamaIndex, or similar.

Proficiency in cloud platforms (AWS, Google Cloud Platform, Azure) and container orchestration (Docker, Kubernetes).

Strong understanding of vector databases (Pinecone, Weaviate, Milvus, FAISS).

Hands-on experience with CI/CD for ML pipelines (MLflow, Kubeflow, Vertex AI, SageMaker).

Knowledge of APIs, microservices, and REST/GraphQL integration.

Familiarity with security & compliance for AI systems (GDPR, HIPAA, enterprise policies).

Preferred Qualifications

Experience with RAG (Retrieval-Augmented Generation) and LLM fine-tuning.

Knowledge of distributed training and inference optimization.

Exposure to prompt optimization and evaluation frameworks.

Prior experience in telecom or large-scale enterprise AI systems.

Thanks & Regards

Tarun Tyagi

Sr. Talent Acquisition Specialist

Enterprise Business Solutions Inc.(EBS)

Email:

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