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Senior AI Engineer β Google Cloud Platform (GCP)
Virtue America
5 hours ago
Full-time
On-site
Raleigh, North Carolina, United States
Job Type: Long-Term Contract
Location: Charlotte, NC / St. Louis, MO (Hybrid)
Experience: 12+ Years
Job Summary
We are seeking an experienced Senior AI Engineer with strong expertise in Google Cloud Platform (GCP), AI/ML engineering, and enterprise architecture. The ideal candidate will have hands-on experience designing, developing, and deploying scalable AI solutions using Python, Natural Language Processing (NLP), Generative AI, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and Agentic AI.
The candidate will be responsible for building enterprise-grade AI applications, designing cloud-based AI architectures, and implementing reliable MLOps and LLMOps practices. This role requires a combination of strong technical development skills and architectural expertise to deliver secure, scalable, and high-performance AI solutions aligned with business objectives.
Key Responsibilities
Design, develop, and deploy enterprise AI/ML solutions using Python and Google Cloud Platform (GCP).
Build and optimize Generative AI applications using LLMs, NLP, RAG pipelines, and Agentic AI frameworks.
Design and implement scalable AI architectures that integrate with enterprise applications, databases, and business workflows.
Develop RAG solutions using vector search, embeddings, semantic search, and enterprise knowledge sources.
Implement AI agents, workflow automation, tool integration, and intelligent decision-support capabilities.
Build and maintain data pipelines and processing workflows to support AI/ML applications.
Implement MLOps and LLMOps practices for model deployment, monitoring, evaluation, versioning, and lifecycle management.
Leverage GCP services and cloud-native technologies to build scalable, reliable, and cost-effective AI applications.
Develop and integrate microservices, REST APIs, and enterprise system interfaces.
Implement security controls, Identity and Access Management (IAM), data protection, and governance practices.
Establish CI/CD pipelines, automated testing, and deployment processes for AI applications.
Collaborate with data engineers, cloud architects, software developers, and business stakeholders to define technical requirements and deliver solutions.
Monitor AI application performance, troubleshoot production issues, and optimize reliability, latency, and cost.
Provide technical leadership, architecture guidance, and best practices for enterprise AI engineering initiatives.
Required Skills
12+ years of experience in IT, software engineering, AI/ML engineering, or a related technical field.
Strong hands-on experience with
Google Cloud Platform (GCP)
and cloud-based application development. Advanced programming skills in
Python . Experience with
Artificial Intelligence, Machine Learning, NLP, Generative AI, and Large Language Models (LLMs) . Strong understanding of
RAG architectures, Agentic AI, vector search, embeddings, and prompt engineering . Experience designing enterprise AI solutions and scalable cloud architectures. Knowledge of
MLOps and LLMOps , including deployment, monitoring, evaluation, and lifecycle management. Experience developing APIs, microservices, and enterprise application integrations. Understanding of cloud security, IAM, data governance, and production deployment practices. Strong problem-solving, system design, communication, and technical leadership skills.
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Google Cloud Platform (GCP)
and cloud-based application development. Advanced programming skills in
Python . Experience with
Artificial Intelligence, Machine Learning, NLP, Generative AI, and Large Language Models (LLMs) . Strong understanding of
RAG architectures, Agentic AI, vector search, embeddings, and prompt engineering . Experience designing enterprise AI solutions and scalable cloud architectures. Knowledge of
MLOps and LLMOps , including deployment, monitoring, evaluation, and lifecycle management. Experience developing APIs, microservices, and enterprise application integrations. Understanding of cloud security, IAM, data governance, and production deployment practices. Strong problem-solving, system design, communication, and technical leadership skills.
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