Job description

Dice is the leading career destination for tech experts at every stage of their careers. Our client, Hexacorp, is seeking the following. Apply via Dice today! Open Positions for direct energy client: Data Engineer, Data Scientist, DevOps Engineer (Google Cloud Platform), LLM Engineer, Data Governance Consultant, Data Historian Engineer, Google Cloud Platform Security Engineer, Google Cloud Platform AVEVA PI System Engineer Please refer my email in response to your application and respond be back with checklist requested! We are looking for a multi-disciplinary AI expert with proven experience in Artificial Intelligence, Large Language Models (LLMs), MLOps/DevOps, and Data Science all within the Google Cloud Platform (Google Cloud Platform) ecosystem. The role requires both strategic AI solutioning and hands-on engineering to build, scale, and operationalize intelligent systems. Key Responsibilities: • Artificial Intelligence (AI) • Research, design, and implement advanced AI/ML algorithms and frameworks. • Deliver enterprise-grade AI/GenAI solutions (chatbots, cognitive automation, knowledge systems). • Evaluate and integrate AI APIs and frameworks (Google AI, Vertex AI, OpenAI, Anthropic, etc.). • LLM Engineering • Fine-tune and deploy LLMs, RAG pipelines, and Generative AI models on Google Cloud Platform. • Optimize prompt engineering, embeddings, and model serving performance. • Ensure secure and scalable integration of LLMs into business applications. • MLOps / DevOps (Google Cloud Platform) • Develop and maintain Vertex AI pipelines for end-to-end ML lifecycle management. • Implement CI/CD automation, model governance, and observability in Google Cloud Platform. • Manage scalable, cost-optimized infrastructure using GKE, Terraform, and Cloud Build. • Data Science (Google Cloud Platform) • Build predictive and prescriptive models using BigQuery ML, TensorFlow, and PyTorch. • Translate business requirements into AI/ML use cases. • Deploy production-ready solutions using Dataflow, Pub/Sub, and Cloud Storage. Required Skills & Experience: • 8+ years in AI/ML/Data Science/DevOps with 5+ years hands-on in Google Cloud Platform. • Strong expertise in AI/ML frameworks (TensorFlow, PyTorch, Scikit-learn) and LLMs. • Hands-on with Vertex AI, BigQuery ML, Cloud Functions, Kubernetes (GKE), and IaC (Terraform). • Strong coding skills in Python, SQL, and ML Ops toolchains. • Proven experience deploying enterprise-scale AI/ML/GenAI systems. Preferred Qualifications: • Google Cloud Platform Certifications (ML Engineer, Data Engineer, Cloud Architect). • Experience in cross-cloud AI deployments (Azure OpenAI, AWS Sagemaker, HuggingFace). • Knowledge of AI governance, security, compliance, and model monitoring. • Prior success in building AI-driven business solutions in production.

Requirements