Job Title: GCP AI Engineer

Company Name: CG-VAK

Job Url: https://www.simplyhired.com/job/3jXKBxXOtZ6wBYPlogqgcgM6XHqsrgPASiTQI2DEyAjivypKuV_DKQ

Job Description: GCP AI Engineer
CG-VAK
Remote

Job Details
Full-time
$80,000 - $100,000 a year
Qualifications
Cloud identity and access management (IAM)
Continuous Delivery (CD) implementation
Kubernetes
Dataproc
Enterprise software
IT system monitoring
Application deployment
Google Cloud Platform
Scalable systems
Prompt engineering
Automating deployment processes
Technical solutions implementation
Model deployment
JavaScript
Firebase
Implementing APIs
Scalability
Agile software development
Amazon CloudWatch
Google Kubernetes Engine
Senior level
AI
Cross-functional collaboration
Cloud monitoring
BigQuery
Python
MLOps
Generative AI
Cross-functional communication
Full Job Description
Job Title: Google Cloud Platform (GCP) AI Lead Engineer

Introduction:

We are seeking an experienced and highly skilled GCP AI/ML & Integration Lead Engineer to design, build, and optimize enterprise-scale AI/ML solutions. As a GCP AI Engineer, you will drive enterprise AI innovation by developing Conversational AI and Generative AI solutions, integrating AI models into enterprise systems, and implementing MLOps best practices on Google Cloud Platform (GCP).

The ideal candidate will have hands-on expertise in Vertex AI, Dialogflow CX, and Firebase/Firestore, with strong programming skills in Python and a deep understanding of prompt engineering, model fine-tuning, and AI lifecycle management. This role combines hands-on technical execution with collaboration across data science, engineering, and business teams to deliver secure, scalable, and high-performing AI solutions.

Key Responsibilities:

Conversational & Generative AI Development: Design and implement end-to-end AI solutions leveraging Dialogflow CX, Vertex AI, and Vertex AI Agent Builder for conversational and generative AI use cases.

Prompt Engineering & Model Fine-Tuning: Develop and optimize prompt strategies and fine-tune large language models (LLMs) using Vertex AI Model Garden and enterprise-specific datasets to improve accuracy and contextual relevance.

Integration & Application Enablement: Integrate AI models and APIs with Firebase, Firestore, Pub/Sub, Dataflow, and Cloud Run to power intelligent, real-time, data-driven applications.

MLOps & Automation: Implement MLOps best practices including CI/CD, model versioning, observability, governance, and security using Vertex AI Pipelines, Cloud Build, and Artifact Registry.

Model Lifecycle & Monitoring: Manage the complete model lifecycle — from development to deployment and monitoring — using Vertex AI, Vector Databases, RAG pipelines, and Vertex AI Model Monitoring.

Observability & Responsible AI: Monitor performance, detect drift, and ensure transparency and fairness using Cloud Logging, Cloud Monitoring, and responsible AI principles.

Technical Leadership & Collaboration: Work closely with AI/ML architects, data engineers, and stakeholders to deliver reliable, production-grade AI systems and provide technical guidance.

Qualifications & Requirements:

Experience: 7+ years in enterprise software, data engineering, or AI/ML engineering, with 1–2 years focused on GCP AI/ML and integration.

Technical Skills:

Programming: Proficiency in Python (JavaScript a plus) for model development, API integration, and automation.
Core GCP Services: Hands-on expertise with Vertex AI, Dialogflow CX, Vertex AI Search and Conversation, Vertex AI Model Garden, Vertex AI Agent Builder.
Generative AI: Proven experience in prompt engineering, LLM fine-tuning, and RAG for enterprise applications.
Integration & Data Tools: Skilled in Firebase/Firestore, BigQuery, Dataflow, Pub/Sub, Cloud Run.
MLOps & Deployment: Experience with Vertex AI Pipelines, Cloud Build, Artifact Registry, and GKE/Kubernetes for scalable deployment automation.
Observability: Proficient in Cloud Logging, Cloud Monitoring, Vertex AI Model Monitoring.
Security & Compliance: Deep understanding of GCP’s security model, IAM, and responsible AI frameworks.
Certifications:

Preferred: GCP Professional Machine Learning Engineer certification.
Alternative: GCP Professional Cloud Architect certification (with commitment to pursue ML Engineer certification).
Preferred Qualifications:

Experience with LangChain, Vertex AI Extensions, or other LLM orchestration frameworks.
Familiarity with Cloud Storage, Dataproc, or other distributed data processing tools.
Understanding of API-first architecture and integration with Apigee/API Gateway.
Personal Attributes:

Self-driven and passionate about applied AI.
Innovative thinker who embraces emerging technologies.
Detail-oriented, proactive, and thrives in dynamic environments.
Ability to work collaboratively in agile, cross-functional teams.
Excellent communication and presentation abilities
Job Type: Full-time

Pay: $80,000.00 - $100,000.00 per year

Experience:

Google Cloud Platform: 3 years (Required)
Ability to Relocate:

Remote: Relocate before starting work (Required)
Work Location: Remote