- Design, delivery, and implementation of Google Cloud Platform (GCP) infrastructure and solutions.
- Architect design and implement large‑scale migration pipelines from on‑prem systems to Azure Data Lake Storage (ADLS).
- GCP Expertise: Strong knowledge of GCP AI/ML services and infrastructure.
- AI/ML Frameworks: Proficiency with TensorFlow or PyTorch.
- Technical Skills: Experience with Python, data modeling, SQL, and APIs.
- Infrastructure as Code: Experience with Terraform for automation.
- Experience: Proven ability in delivering AI/ML solutions in a cloud environment
- Experience with performing analytics on data for stakeholders.
- Experience in ingesting data from different sources using in Azure ADF
- Ensure reliable handling of high‑volume unstructured data with performance and cost efficiency.
- Implement data quality checks, logging, and traceability to support audit and compliance needs.
- Experience in transforming data using Azure Databricks & Delta lake
- Architecture & Design: Design enterprise‑grade AI platforms, including RAG (Retrieval‑Augmented Generation) and agentic solutions.
- GCP Implementation: Develop AI models using Vertex AI and Gemini, ensuring security and performance.
- Pipeline Development: Build and manage data pipelines, model lifecycle, CI/CD, and MLOps/LLMOps with Cloud Build and Vertex AI Pipelines.
- Cloud Infrastructure: Utilize GKE, Cloud Run, and BigQuery for robust application deployment.
- Strategy & Governance: Implement AI safety features, monitor model performance, and manage costs.
Job Description
Must Have Technical/Functional Skills
- Design, delivery, and implementation of Google Cloud Platform (GCP) infrastructure and solutions.
- Architect design and implement large‑scale migration pipelines from on‑prem systems to Azure Data Lake Storage (ADLS).
- Architect experience in generating data pipelines in Azure ADF
- GCP Expertise: Strong knowledge of GCP AI/ML services and infrastructure.
- AI/ML Frameworks: Proficiency with TensorFlow or PyTorch.
- Technical Skills: Experience with Python, data modeling, SQL, and APIs.
- Infrastructure as Code: Experience with Terraform for automation.
- Experience: Proven ability in delivering AI/ML solutions in a cloud environment
- Experience with performing analytics on data for stakeholders.
- Experience in ingesting data from different sources using in Azure ADF
- Ensure reliable handling of high‑volume unstructured data with performance and cost efficiency.
- Implement data quality checks, logging, and traceability to support audit and compliance needs.
- Experience in transforming data using Azure Databricks & Delta lake
Roles & Responsibilities
- Architecture & Design: Design enterprise‑grade AI platforms, including RAG (Retrieval‑Augmented Generation) and agentic solutions.
- GCP Implementation: Develop AI models using Vertex AI and Gemini, ensuring security and performance.
- Pipeline Development: Build and manage data pipelines, model lifecycle, CI/CD, and MLOps/LLMOps with Cloud Build and Vertex AI Pipelines.
- Cloud Infrastructure: Utilize GKE, Cloud Run, and BigQuery for robust application deployment.
- Strategy & Governance: Implement AI safety features, monitor model performance, and manage costs.
Salary Range: $120,000 -$140,000 year
TCS Employee Benefits Summary
- Discretionary Annual Incentive.
- Comprehensive Medical Coverage: Medical & Health, Dental & Vision, Disability Planning & Insurance, Pet Insurance Plans.
- Family Support: Maternal & Parental Leaves.
- Insurance Options: Auto & Home Insurance, Identity Theft Protection.
- Convenience & Professional Growth: Commuter Benefits & Certification & amp; Training Reimbursement.
- Time Off: Vacation, Time Off, Sick Leave & Holidays.
- Legal & Financial Assistance: Legal Assistance, 401K Plan, Performance Bonus, College Fund, Student Loan Refinancing.
Qualifications:
BACHELOR OF COMPUTER SCIENCE
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