Design and Deliver AI/ML and Data-Driven Solutions
Architect and implement scalable AI and ML solutions on Google Cloud Platform using Vertex AI, BigQuery, Cloud Run, and other GCP services.
Collaborate with clients to assess business challenges and translate them into technical AI/ML solutions.
Build, deploy, and operationalize machine learning models in production environments.
Develop data pipelines and feature engineering workflows using Dataflow, Dataproc, Pub/Sub, and Cloud Storage.
Integrate AI capabilities such as natural language processing, computer vision, and generative AI into enterprise systems.
Collaborate with Cross-Functional Teams
Partner with Cloud Architects, Data Engineers, and Project Managers to ensure end-to-end delivery of AI-driven solutions.
Work closely with Client Success Managers to ensure solutions align with client goals and deliver measurable outcomes.
Engage with Google Cloud specialists for complex technical implementations and proof-of-concept initiatives.
Drive Innovation and Technical Excellence
Stay current with the latest AI/ML, data analytics, and generative AI advancements within Google Cloud and the broader industry.
Contribute to internal knowledge sharing, reusable code libraries, and best practices documentation.
Support pre-sales efforts by scoping AI projects and developing prototypes or demos for prospective clients.
Serve as a Trusted Technical Advisor
Guide clients through the adoption of AI and ML technologies, balancing innovation with practical business value.
Present complex technical concepts to executive audiences and non-technical stakeholders.
Provide training and mentorship to internal teams and clients on Google Cloud AI/ML tools and best practices.
Minimum Qualifications:
Experience & Track Record
4+ years of experience in designing and deploying AI/ML or data-driven solutions, preferably within cloud environments.
Hands-on experience with Google Cloud AI/ML services (Vertex AI, AutoML, BigQuery ML).
Strong background in data processing, machine learning lifecycle management, and model operationalization.
Experience developing proof-of-concepts or production-grade AI applications using Python and frameworks such as TensorFlow, PyTorch, or scikit-learn.
Demonstrated ability to work collaboratively with technical and business teams in client-facing roles.
Google Cloud Platform Expertise
Google Cloud Professional Machine Learning Engineer or Professional Data Engineer certification preferred.
If not currently certified, commitment to achieve Associate Cloud Engineer within 3 months and Professional Machine Learning Engineer within 12 months of hire.
Strong familiarity with key GCP services: BigQuery, Vertex AI, Dataflow, Cloud Run, Cloud Functions, and Cloud Storage.
Understanding of MLOps best practices, model monitoring, and continuous training workflows.
Technical Foundation
Proficiency in Python and SQL; familiarity with notebooks such as Vertex AI Workbench or Jupyter.
Experience with data pipeline orchestration using Composer, Dataflow, or Airflow.
Knowledge of API design, microservices, and containerization using Docker and Kubernetes (GKE).
Understanding of responsible AI principles, data governance, and security best practices in cloud environments.
Core Competencies
Excellent communication skills and ability to translate technical AI concepts into business value.
Strong analytical and problem-solving mindset with attention to detail.
Curiosity-driven and proactive in identifying opportunities for automation and optimization.
Bachelor’s degree in Computer Science, Data Science, Engineering, or related field (or equivalent practical experience).
Preferred Qualifications:
Google Cloud Professional certifications (Machine Learning Engineer, Data Engineer, or Cloud Architect).
Experience with generative AI APIs, LangChain, or custom model fine-tuning on Vertex AI.
Familiarity with data analytics, business intelligence, or visualization tools (Looker, Data Studio, Tableau).
Experience with MLOps frameworks and CI/CD for ML (Vertex AI Pipelines, MLflow, Kubeflow).
Previous consulting or professional services experience in a client-facing technical role.
Exposure to compliance and data privacy standards (SOC 2, HIPAA, GDPR).
About the job
As an AI Solutions Engineer at Premier Cloud, you’ll design and implement advanced AI/ML and data-driven solutions on Google Cloud. You’ll work directly with clients to understand business challenges, translate them into scalable technical architectures, and deliver production-ready AI systems using tools such as Vertex AI, BigQuery, Dataflow, and Cloud Run. You’ll collaborate with cross-functional teams—including architects, data engineers, project managers, and Google Cloud specialists—to drive end-to-end solution delivery. This role combines hands-on technical execution with strategic guidance, ensuring clients adopt AI technologies effectively and confidently.
Additional Information
Competitive Compensation: A package that reflects your experience and impact.
Growth & Development: Continuous training, certifications, and opportunities to work on cutting-edge AI and Google Cloud projects.
Collaboration with Google: Work directly with Google teams on transformative AI initiatives.
Comprehensive Benefits: Including health coverage, paid time off, and relocation assistance (if applicable).
Work Environment: Flexible remote work supported by premium company-issued technology and a strong culture of trust and autonomy.
Premier Cloud is an equal-opportunity employer that values and celebrates diversity. We welcome applicants of all backgrounds, experiences, perspectives, genders, ethnicities, abilities, orientations, and identities. We're committed to creating an inclusive environment where every team member can thrive, contribute their unique perspectives, and grow their careers. We encourage applications from candidates who may not meet every qualification listed but bring valuable experience, perspectives, and passion for cloud and AI technology.
