Azure AI Engineer-End to End Engineering Lead

GSPANN Technologies, Inc; Fremont (CA); On-site; USD 180,000 - 240,000; Full time

Job summary

GSPANN Technologies, Inc. in Fremont, CA seeks an experienced Azure AI Engineer / End-to-End Engineering Lead to design, develop, deploy, and operate production-grade AI/ML solutions on Microsoft Azure.

The role emphasizes Azure AI, DevOps, MLOps, and cloud engineering with enterprise-scale delivery. The ideal candidate will guide the complete lifecycle from development and infrastructure automation to deployment, monitoring, and production operations, collaborating with data scientists and

Qualifications

• 12–15+ years of overall technology experience.
• Hands-on experience designing AI/ML solutions on Microsoft Azure.
• Experience with MLOps, DevOps, CI/CD, and enterprise AI/ML deployment strategies.
• Hands-on with Azure DevOps Pipelines and/or GitHub Actions.
• Strong knowledge of Docker, Kubernetes, and AKS.
• IaC experience with Terraform and/or Bicep.
• Experience with Azure observability tools: Monitor, Application Insights, Log Analytics.
• Experience securing cloud apps with Azure Key Vault and Entra ID.
• Experience with Azure Data Lake Gen2, Data Factory, Databricks, Synapse, or similar.
• Ability to work in PST hours; Fremont, CA local candidates preferred.

Responsibilities

• Design, develop, deploy, and operate production-grade AI/ML solutions on Microsoft Azure.
• Design and implement end-to-end MLOps pipelines using Azure Machine Learning.
• Design and implement CI/CD pipelines for AI/ML apps and infrastructure.
• Build deployment pipelines using Azure DevOps Pipelines and/or GitHub Actions.
• Manage separate deployment strategies across Dev, Test, UAT, Staging, and Production environments.
• Develop infrastructure with IaC using Terraform and/or Bicep.
• Build and deploy containerized AI/ML apps with Docker and Kubernetes/AKS.
• Integrate AI/ML with Azure Data Lake Gen2, Data Factory, Databricks, Synapse.
• Implement observability with Azure Monitor, App Insights, Log Analytics.
• Secure AI/ML environments using Azure Key Vault and Entra ID.
• Collaborate with data scientists, engineers, and stakeholders to deliver scalable solutions.
• Provide technical leadership across the end-to-end AI lifecycle.
• Establish best practices for AI/ML development, MLOps, DevOps, security, and reliability.

Skills

Azure AI

DevOps

MLOps

CI/CD

Docker

Kubernetes

AKS

Terraform

Bicep

Azure Monitor

Application Insights

Log Analytics

Azure Data Lake Gen2

Azure Data Factory

Databricks

Synapse

Azure Key Vault

Entra ID

PST hours

Tools

Azure DevOps

GitHub Actions

Terraform

Bicep

AKS

Docker

Kubernetes

Azure Databricks

Azure Data Factory

Job description

Headquartered in California, U.S.A., GSPANN is a leading provider of consulting and IT services to global clients. We specialize in helping clients transform their IT capabilities, optimize business practices, and drive operational efficiency across industries such as retail, high-technology, and manufacturing. With five global delivery centers and over 1,900 employees, we combine the personalized approach of a boutique consultancy with the extensive capabilities of a large IT services firm.

Job Type & Duration: Long-Term Contract

Job Location: Fremont, CA (Preferred for Onsite/Hybrid Work)

Job Summary:

We are looking for a highly skilled Azure AI Engineer / End-to-End Engineering Lead with strong hands‑on expertise in Azure AI, DevOps, MLOps, and cloud engineering to design, develop, deploy, and operate production‑grade AI and Machine Learning solutions on Microsoft Azure.

The ideal candidate will have extensive experience building enterprise‑grade AI/ML solutions using Azure Machine Learning, Azure AI Foundry, Azure OpenAI, Azure AI Search, Azure AI Services, and related Azure technologies. This role requires a strong engineering mindset with the ability to lead solutions across the complete AI/ML lifecycle, from development and infrastructure automation through deployment, monitoring, and production operations.

Key Responsibilities:

• Design, develop, deploy, and operate production‑grade AI and Machine Learning solutions on Microsoft Azure.
• Design and implement end-to-end MLOps pipelines using Azure Machine Learning.
• Design and implement enterprise‑grade CI/CD pipelines for AI/ML applications and infrastructure.
• Build and manage deployment pipelines using Azure DevOps Pipelines and/or GitHub Actions.
• Establish and manage separate deployment strategies across Dev, Test, UAT, Staging, and Production environments.
• Develop and manage infrastructure using Infrastructure as Code (IaC) with Terraform and/or Bicep.
• Build and deploy containerized AI/ML applications using Docker and Kubernetes/AKS.
• Integrate AI/ML solutions with Azure Data Lake Storage Gen2, Azure Data Factory, Azure Databricks, Synapse, or equivalent data platforms.
• Implement enterprise‑grade observability and monitoring using Azure Monitor, Application Insights, Log Analytics, and related Azure services.
• Implement secure AI/ML environments using Azure Key Vault, Microsoft Entra ID, and other Azure security capabilities.
• Collaborate with data scientists, software engineers, DevOps engineers, architects, and business stakeholders to deliver scalable AI/ML solutions.
• Provide technical leadership across the end-to-end AI engineering lifecycle, including architecture, development, automation, deployment, monitoring, and production support.
• Establish engineering best practices for AI/ML application development, MLOps, DevOps, security, scalability, and reliability.

Qualifications:

• 12–15+ years of overall technology experience with strong hands‑on engineering expertise.
• Strong hands‑on experience designing and implementing AI/ML solutions on Microsoft Azure.
• Strong experience with MLOps, DevOps, CI/CD, and enterprise AI/ML deployment strategies.
• Hands‑on experience with Azure DevOps Pipelines and/or GitHub Actions.
• Strong knowledge of Docker, Kubernetes, and Azure Kubernetes Service (AKS).
• Experience with Terraform and/or Bicep for Infrastructure as Code.
• Strong experience with Azure observability and monitoring tools, including Azure Monitor, Application Insights, and Log Analytics.
• Experience securing cloud applications using Azure Key Vault and Microsoft Entra ID.
• Experience working with Azure Data Lake Storage Gen2, Azure Data Factory, Azure Databricks, Synapse, or equivalent data platforms.
• Strong understanding of enterprise cloud architecture, scalable systems, security, reliability, and production operations.
• Excellent problem‑solving, communication, collaboration, and technical leadership skills.
• Ability to work effectively in PST hours and collaborate with distributed engineering and business teams.
• Local candidates in the Fremont, CA area are preferred for potential onsite/hybrid requirements.

Working at GSPANN

GSPANN is a diverse, prosperous, and rewarding place to work. We provide competitive benefits, educational assistance, and career growth opportunities to our employees. Every employee is valued for their talent and contribution. Working with us will give you an opportunity to work globally with some of the best brands in the industry.

The company does and will take affirmative action to employ and advance in the employment of individuals with disabilities and protected veterans and to treat qualified individuals without discrimination based on their physical or mental disability status. GSPANN is an equal opportunity employer for minorities/females/veterans/disabled.