AI Platform Principal Engineer – Google Cloud Platform
Hartford, North Carolina, United States of America
Full Time
3 weeks ago
$168,400 - $252,600 USD
Visa Sponsor
Key skills
AWSAzureBigQueryCloudDockerETLGoogle Cloud PlatformNoSQLPythonTerraformAIMLDeep LearningNatural Language ProcessingGenerative AIGenAILLMRAGLangChainLlamaIndexAgenticLangGraphData EngineeringUnit TestingIntegration TestingGCPGoogle CloudServerlessGKEAPI GatewayCloud FunctionsAgileCI/CDCommunication
About this role
Role Overview
- Develop value-added features tailored to company specific work, above and beyond the core capabilities of the cloud platform and relevant vendor tools.
- Research, experiment with, and implement suitable GenAI algorithms, tools, and technologies.
- Explore new services and capabilities in AWS, Google Cloud Platform, and Azure to support GenAI and ML services.
- Enhance platform functionality with strong engineering expertise in AI, ML, Agentic Frameworks, and modern data technologies.
- Develop and promote best practices in AI, ML, and data engineering across teams.
- Architect and design end-to-end solutions at a component level.
- Collaborate with partners in Enterprise Data, Data Science, Business, Cloud Enablement Team, and Enterprise Architecture teams.
- Manage engineering tasks, driving execution, and optimizing workflows with minimal guidance.
- Provide technical mentorship and career growth opportunities for team members.
- Review work of systems-level engineers to calibrate deliverables against project and business expectations.
Requirements
- Bachelor's degree in Computer Science, Computer Engineering, or a technical field
- 10+ years building and shipping software and/or platform solutions for enterprises
- Programming experience with Python is preferred
- 5+ years of experience with Terraform
- Experience building libraries, frameworks or platforms used across multiple teams is a plus
- Proven experience with Google Cloud Platform (GCP)
- Experience with GCP BigQuery, Cloud Functions, AI Platform, API Gateway, GKE/Docker is a must
- Proven experience in working with other cloud providers such as AWS cloud is a plus
- Experience with CI/CD pipelines, Automated Testing, Automated Deployments, Agile methodologies, Unit Testing, and Integration Testing tools
- Experience with building scalable serverless applications (real-time/batch) using cloud technologies
- Knowledge of distributed NoSQL database systems and data engineering, ETL technology
- Conversational UX/UI design (chatbots) and Human-Agent-Interaction (HAI) is a plus
- Experience with IR, vector embedding, and Hybrid/Semantic search technologies
- Knowledge about customization techniques across various stages of the RAG pipeline, including model fine-tuning, retrieval re-ranking, HNSW, and product quantization is a plus
- Experience with embeddings, ANN/KNN, vector stores, database optimization, & performance tuning is a plus
- Experience with LLM orchestration frameworks like Langchain, LlamaIndex, LangSmith, LangGraph, Google Agent Development Kit, is a plus
- Experience with Generative AI Guardrails, responsible AI, adversarial attack mitigation, and red teaming is a plus
- Foundational understanding of Natural Language Processing and Deep Learning
- Excellent problem-solving skills and the ability to work in a collaborative team environment
- Excellent communication skills
- Candidate must be authorized to work in the US without company sponsorship.
- The company will not support the STEM OPT I-983 Training Plan endorsement for this position.
Tech Stack
- AWS
- Azure
- BigQuery
- Cloud
- Docker
- ETL
- Google Cloud Platform
- NoSQL
- Python
- Terraform
Benefits
- Other rewards may include short-term or annual bonuses
- long-term incentives
- and on-the-spot recognition